Study Guide

Objective

After completing the module, the student is able:
- to understand the technical asset pipeline for 2D game graphics
- to create 2D content for video games and other digital media
- to use various software for content creation
- to understand the roles and tasks for 2D graphics in the game industry

Content

- 2D tools
- 2D asset creation
- 2D animation tools and techniques
- UI graphics and tools
- Modern approaches for 2D content creation for game engines

Materials

Lecturer's material and live sessions. Software manufacturer specific online references and materials
Additional material and reading material shared through Itslearning for each week's theme.
We will be using Adobe Photoshop and Illustrator. You can utilize the lab classroom each day from 4:00 pm until 8:00 pm or you can buy student licence from Adobe. Read more about the Adobe TUAS Student licence in Messi intranet.

Teaching methods

The course will be delivered through close contact sessions and the core learning will take place in a tutorial fashion with laboratory assignments and homework.

Although peer-assisted learning is encouraged, students are expected to produce individual deliverable (in other words, no group work).

The students are expected to give peer feedback on specified laboratory assignments and homework.

The course will be using Itslearning as the learning platform

Exam schedules

No exam dates;
This course does not have any retake possibilities. Failing the course means that students will have to repeat it the following year.

International connections

This course leans on CDIO principles and takes a project-based learning approach.

Completion alternatives

Competence demonstration, if you have experience from industry or experience that is compatible with the course content. Discuss with the instructor when the course starts for demonstration

Student workload

This course requires students to work 135 hours and is divided as follows:
- Contact sessions and Instructed laboratory work 48 hours
- Individual work with assignments and material review 86 hours
All the course work is individual

Content scheduling

Course starts on 2.9.2024 and ends 24.10.2024. The course is held onsite at campus with close contact. Mandatory participation for 70% of the close contact and laboratory sessions.

Each week Monday and Thursday will be contact session at laboratory C3031. The laboratory assignments and home works is related to the topic of the week.
The Schedule:
Week 36 Course Introduction, 2D Graphics in Games, intro to Adobe Photoshop
Week 37 Tools For 2D Graphics: Photoshop continues
Week 38 Tools For 2D Graphics: Vector graphics Adobe Photoshop&Illustrator
Week 39 Tools For 2D Graphics: Illustrator continues
Week 40 Unity 2D: tools & techniques
Week 41 Unity 2D: tools & techniques
Week 42 WORK ON YOUR OWN - 2D Game Art
Week 43 Unity 2D: tools & techniques


Assignments changes every week and assignments needs to returned before next weeks live session. No feedback available for late submission. Last assignment must be returned before 31.10.2024

Further information

Mandatory participation for 70% of the close contact and laboratory sessions.
Participation is mandatory due: laboratory oriented approach, software licence requirements, peer assisted learning, immediate support and feedback, engagement and motivation, consistency and discipline.

Evaluation scale

H-5

Assessment methods and criteria

The assessment will be based on the individual assignments submitted in the Itslearning workspace. Mandatory participation for 70% of the close contact and laboratory sessions.

The lecturer evaluates each assignments from 0-5. To pass the course, students are expected to submit at least 70 % of the assignments. Final grade will be average of assignment grades multiplied by return percent (non-returned assignments are counted as 0) and participation percentage. Active participation to the course, discussion and assignments will affect positively.

The students are expected to give peer feedback on specified laboratory assignments and homework. Failing to participate to the peer feedback will result -1 grade to the final evaluation.
Late submission will affect negatively to the evaluation. Last assignment must be returned before 30.10.2024

Assessment criteria, fail (0)

Participation for the close contact and laboratory sessions is less than 70%.
Student submits less than 70% of the assignments.

Assessment criteria, satisfactory (1-2)

Participation for the close contact and laboratory sessions is more than 70%.
The average is of the submitted assignments and the submission percentage equals 1-2
The quality of the submitted assignments are poor and it is visible that the student has not spent the required time with the assignment.

Assessment criteria, good (3-4)

Participation for the close contact and laboratory sessions is more than 80%.
The average is of the submitted assignments and the submission percentage equals 3-4
The quality of the submitted assignments are good and it is visible that the student has spent the required time with the assignment but the student has not challenged his/her skills or the assignment lacks the final effort to improve it.

Assessment criteria, excellent (5)

Participation for the close contact and laboratory sessions is more than 90%.
The average is of the submitted assignments and the submission percentage equals 5
The quality of the submitted assignments are excellent and it is visible that the student has spent the required time or more with the assignment. The student has challenged his/her skills and researched more about the topic to improve the end result and his/her skills.

Objective

After completing the module, the student is able:
- to understand the technical asset pipeline for 3D game graphics
- to create 3D content for video games other digital media
- to use various software for content creation
- to understand the roles and tasks for 3D graphics in the game industry

Content

- 3D modelling and animation for game engines
- 3D asset creation
- Character modelling
- Modular design
- Lighting and texturing techniques and tools in game engines
- Modern approaches for 3D content creation for game engines

Materials

Lecturer's material and live sessions. Software manufacturer specific online references and materials
Group chat on Discord. Additional material and reading material shared through Itslearning for each week's theme.

Teaching methods

The course will be delivered through contact sessions and the core learning will take place in a tutorial fashion with laboratory assignments and homework.

Although peer-assisted learning is encouraged, students are expected to produce individual deliverables (in other words, no group work).

The students are expected to give peer feedback on specified laboratory assignments and homework.

The course will be using Itslearning as the learning platform.

Exam schedules

There are no exams for this course.

This course does not have any retake possibilities. Failing the course means that students will have to repeat it the following year.

International connections

This course leans on CDIO principles and takes a project-based learning approach.

Completion alternatives

Competence demonstration, if you have experience from industry or experience that is compatible with the course content contact the lecturer.

Student workload

This course requires students to work 135 hours and is divided as follows:
- Contact sessions and instructed laboratory work 49 hours
- Individual homework 86 hours
All the course work is individual.
Mandatory participation for 70% of the sessions.

Content scheduling

Course starts on 28.10.2024 and ends 12.12.2024. The course will be held onsite at game laboratory. Tasks and guidance are given at the laboratory classroom. Mandatory participation for 70% of the sessions.

Each Monday and Thursday contact session in the laboratory C3031. The laboratory assignments and homework are related to the topic of the week.

Week 44 Course Introduction, 3D Graphics in Games, Game engines & tools, content creation inside game engine.
Week 45 Unity: Render pipelines, asset preparation, shader & VFX graph
Week 46 Unity: Lighting in Unity, post process etc
Week 47 Substance Sampler, Authoring PBR materials & Substance in Game Engines
Week 48 Substance Painter & game asset pipeline
Week 49 Substance Painter & game asset pipeline
Week 50 Substance Designer
Week 51 Personal work on assignments.

Assignment changes each week and assignment needs to be returned before next week’s live session. Late submission will affect negatively to the evaluation. Last assignment must be returned before 19.12.2023.

Further information

All communication trough Itslearning.
This course is prioritized for Game and Interactive Technology Students. Additional students can join only if there are available seats in the game lab.
Recommended Prerequisites:
Game Development Essentials
Introduction to Game Development Tools
Project Course in Game Development
Strong recommendation for basics of 3D Modeling

Mandatory participation for 70% of the sessions.
Participation is mandatory due: laboratory oriented approach, software licence requirements, peer assisted learning, immediate support and feedback, engagement and motivation, consistency and discipline.

Evaluation scale

H-5

Assessment methods and criteria

The assessment will be based on the individual assignments submitted in the Itslearning workspace.
The lecturer evaluates each assignments from 0-5. To pass the course, students are expected to submit at least 70 % of the assignments. Final grade will be average of assignment grades multiplied by return percent (non-returned assignments are counted as 0). Active participation to the course, discussion and assignments will affect positively.

The students are expected to give peer feedback on specified laboratory assignments and homework. Failing to participate to the peer feedback will result -1 grade to the final evaluation.

Assignment changes each week and assignment needs to returned before next weeks live session.No feedback for late assignment submissions. Last assignment must be returned before 19.12.2024

Assessment criteria, fail (0)

Student submits less than 70% of the assignments and participation is less than 70% to the sessions.

Assessment criteria, satisfactory (1-2)

The student hast participated at least 70% to the sessions.
The average is of the submitted assignments and the submission percentage equals 1-2.
The quality of the submitted assignments are poor and it is visible that the student has not spent the required time with the assignment.

Assessment criteria, good (3-4)

The student hast participated at least 80% to the sessions.
The average is of the submitted assignments and the submission percentage equals 3-4.
The quality of the submitted assignments are good and it is visible that the student has spent the required time with the assignment but the student has not challenged his/her skills or the assignment lacks the final effort to improve it.

Assessment criteria, excellent (5)

The student hast participated at least 90% to the sessions.
The average is of the submitted assignments and the submission percentage equals 5.
The quality of the submitted assignments are excellent and it is visible that the student has spent the required time or more with the assignment. The student has challenged his/her skills and researched more about the topic to improve the end result.

Objective

After completing this course the student is able
- to create 3D models and understand 3D modeling workflow
- to craft textures and materials for the models
- to animate objects and characters

Content

- Fundamentals of 3D modeling techniques
- Introduction to texturing, materials and lighting for 3D content creation
- Basics in animating techniques

Materials

Contact sessions 3h per week. Group chat on Discord for those who are interested. Course material and information shared through itslearning.

Teaching methods

Weekly contact sessions and weekly assignments.

Exam schedules

There are no exams on this coure.

Completion alternatives

Competence demonstration, if you have experience from industry and/or experience that is compatible with the course content

Student workload

One contact session 3h. One prelab and one weekly assignment per week. Prelab is starter for the weekly assignment and it need to be done before contact session.

Estimated work time is 9 hours every week (3 hours in contact session and 6 hours independent work), 126 hours total.

Content scheduling

Content is separated in three main categories: Modeling, Materials and Animation. All work is done with Blender.

Course starts at week 3 and last contact session is at week 17 Totally 14 times. Assignments changes every week and assignments need to be returned before next weeks contact session.

Lesson 1: Blender GUI and primitives
Lesson 2: Modeling - "box modeling"
Lesson 3: Modeling - from scratch "polygon modeling"
Lesson 4: Modeling - Boolean modeling
Lesson 5: Modeling - retopology
Lesson 6: Modeling - Sculpting
Lesson 7: Modeling - Own modeling work
Lesson 8: Materials - Materials and Lightning (Cycles)
Lesson 9: Materials - UV map and textures
Lesson 10: Materials - Texture baking
Lesson 11: Animation - Animation tools
Lesson 12: Animation - Animation with bone parenting
Lesson 13: Animation - Character rigging
Lesson 14: Animation - Walk cycle

Further information

Course material and information shared through itslearning.

Evaluation scale

H-5

Assessment methods and criteria

Assessment will be based on the individual assignments submitted in the itslearning course platform.

Teacher evaluates the assignments. To pass the course, students are expected to turn in at least 75 % of the assignments. Final grade will be average of assignment grades multiplied by return percent (non-returned assignments are counted as 0).

Assessment criteria, fail (0)

Student submits less than 75% of the assignments

Assessment criteria, satisfactory (1-2)

The average is of the submitted assignments and the submission percentage equals 1-2
The quality of the submitted assignments are poor and it is visible that the student has not spent the required time with the assignment

Assessment criteria, good (3-4)

The average is of the submitted assignments and the submission percentage equals 3-4
The quality of the submitted assignments are good and it is visible that the student has spent the required time with the assignment but the student has not challenged his/her skills or the assignment lacks the final effort to improve it.

Assessment criteria, excellent (5)

The average is of the submitted assignments and the submission percentage equals 5
The quality of the submitted assignments are excellent and it is visible that the student has spent the required time or more with the assignment. The student has challenged his/her skills and researched more about the topic to improve the end result

Objective

After completing the course the student can:
Implement a desktop or a web application for an assigned task.
Program efficiently in a team using professional tools.
Reuse code, utilize libraries, and/or application platforms and application frameworks.
Write code from UML diagrams or implement user stories.
Understand some common design patterns.

Content

An assignment for a desktop or a web application.
Elaborating on programming language and features suitable for the application.
Learning and utilising one or more design patterns.
Using professional coding and version control tools.
Re-using code and utilising libraries, frameworks and/or platforms.
Developing a desktop or a web application as a team work.

Materials

Text books: Course is based on:

"Spring Boot in Action" by Craig Walls:
This book provides a comprehensive guide to building web applications, including RESTful web services, using Spring Boot. It covers the fundamentals of Spring Boot and how to create RESTful APIs with it.

"Spring Microservices in Action" by John Carnell:
While this book focuses on microservices architecture, it extensively covers creating RESTful APIs with Spring Boot as a fundamental part of building microservices. It's a great choice if you're interested in microservices-based RESTful services.

"Mastering Spring Boot 2.0" by Dinesh Rajput:
This book covers advanced topics related to Spring Boot, including RESTful web services. It's suitable for those who have a basic understanding of Spring Boot and want to dive deeper into building RESTful APIs.

"Spring REST" by Balaji Varanasi and Sudha Belida:
This book, mentioned earlier in the context of RESTful web services in general, is also a good resource if you're specifically interested in using Spring for building RESTful APIs.

"Building RESTful Web Services with Spring 5" by Ludovic Dewailly and Alexandre Chapellon:
This book focuses on Spring 5 and covers building RESTful web services using the latest features of the Spring framework, making it a valuable resource for staying up-to-date with Spring technology.

"Spring Boot 2.0 Cookbook" by Alex Antonov:
This book provides practical recipes for building various types of applications with Spring Boot, including RESTful web services. It's a hands-on guide with real-world examples.

More course material and assignments implementation instructions will be provided during learning period.

Teaching methods

- Weekly face-to-face meetings with lectures and small group work
- Learning by doing and experimenting (Implementation assignments, project work)
- Small group work and peer learning
- Self-study material and FLIP classroom

Exam schedules

No exam

International connections

Learning by doing and FLIP classrooms

Completion alternatives

Ask the teacher about possible alternative methods of completion

Student workload

Contact hours
- Course introduction: 3 hours
- 13 times 3h theory and practice: 13 x 3h = 39 hours
- FLIP classroom 7 X 2h = 14

Home work:
- Working with assignments: approximately 80 hours

Total: approximately 135 hours

Content scheduling

The course content is divided into four learning objectives(CLOs):

CLO1 Develop applications interacting with cloud-based/regular SQL databases using the latest ORM frameworks:
Database Connectivity using JDBC
1.1 Create a database connection
1.2 Create Statement Objects
1.3 Perform SQL Commands
1.4 Manipulate databases

Database Connectivity using Spring Boot Data JPA
1.5 Implement Database connectivity using Spring Boot Data JPA
1.6 Manipulate persistent data using Spring Boot Data JPA

NoSQL Database Connectivity using ORM
1.7 Compare JSON with XML
1.8 Implement a NoSQL Database connectivity using Spring Boot Data JPA

CLO2 Apply services architecture to implement REST based web services and micro services:
Web services and SOA (Service Oriented Architecture) (optional)
2.1 Explain SOA advantages and Principles
2.2 Explain the limitations of software capabilities
2.3 Implement SOAP Web services

Backend web development RESTful web services
2.4 Introduce the Representational State Transfer (REST)
2.5 Use HTTP Methods for CRUD operations
2.6 Analyze HTTP Status Codes

RESTful web services
2.7 Configure Spring Boot Application
2.8 Create RESTful web services using Spring Boot Framework
2.9 Connect RESTful web services using Spring Boot Framework with a database
2.10 Implement entities, JPA Repository, and controllers
2.11 Build a Restful API
2.12 Test Restful API

CLO3 Analyze responsive web apps using latest UI frameworks to interact with web services:
Angular as Front-End framework
3.1 Introduce Angular Components
3.2 Implement Angular Services
3.3 Analyze an application that consumes the REST API Web service

CLO4 Deploy micro services using Dockers:
Service Virtualization Tools
4.1 Explain Service Virtualization
4.2 Introduce Docker
4.3 Create Docker Container
4.4 Deploy Application in Docker



We will use the following languages, protocols and tools:
Eclipse
MySQL
NodeJS
Spring boot
JPA
JSON
XML
REST
Angular (HTML, CSS, TS)
Docker

Further information

Course material and assignments during learning period.

Evaluation scale

H-5

Assessment methods and criteria

Assignments:
Individual assignments: 80 points
The group project work: 20 points.

The assignments must be returned by the deadline to get the points. The assignments returned after the deadline will give you only half of the points.

Demonstrations of exercises during the contact session is mandatory without demonstration you will lose 50% of your marks.

Assessment criteria, fail (0)

0-49 (0)

Assessment criteria, satisfactory (1-2)

50-59 (1)
60-69 (2)

Assessment criteria, good (3-4)

70-79 (3)
80-89 (4)

Assessment criteria, excellent (5)

90-100 (5)

Objective

Further deepening knowledge of more challenging ICT project work and the most used methods and technologies of software projects.

Content

Project work in an international project team in ICT projects.
Substance knowledge of different ICT field -related topics.
Working life skills (team working, communication, time management, professional attitude and taking responsibility) and problem-solving skills.

Materials

Various internet sources, links & descriptions online.
Lecture slides.
theFIRMA's and course's Itslearning.

Teaching methods

Lectures, group work and independent work, project work, online/on-site activities

Exam schedules

No exam.

To successfully pass the course, students must achieve passing grade in both the assignments and the project work components.

If a student does not pass the course, they are required to re-enroll and participate in the course during the next available offering, typically the following academic year.

International connections

Practical assignments and reports
Project work
Self study

Completion alternatives

Project work part can be done in a company, if student has a ICT-related job. This has to be agreed separately with responsible teacher.

Student workload

Lectures, exercises on lectures and small group meetings: 72 hours
Assignments and self study: 63 hours
Project work 135 hours, which includes mandatory 40 hours of theFIRMA weekly meetings for project managers. Also, ICT guest lectures and theFIRMA Tech-club hours are counted to project work hours.

TOTAL 270 hours

Majority of project work is done on-site.

Content scheduling

This course deepens further knowledge of challenging ICT project work and the most used methods, standards and technologies of software projects. Students will team up for a project work on customer projects related to ICT field. Customer projects develop students’ working life skills (among others: technical, team working, communication, time management, professional attitude and taking responsibility) and problem solving skills.

Project teams are usually international and the official communication language is usually English. This develops students’ ability to multicultural communication and collaboration.

Further information

The course's and theFIRMA itslearning and Microsoft Teams.

Evaluation scale

H-5

Assessment methods and criteria

The course consists of two parts, the theory part and the project work part. Both parts need to be passed to pass the course.

The theory part includes 6 assignments:
- All of the assignments are assessed with 0-30 points. Thus, the maximum number of points from the assignments are 180.
Late submission for the assignments will reduce the points by 50%.

The presence in the theory lectures and small group meetings are marked down. The first and last lectures give the student 2 points, other lectures and small group meetings are worth 1 points. In total, there are 30 points from presence.

Altogether these will give the students the maximum of 210 points. These points are evaluated in the following way:
Fail: 0-59 points
grade 1: 60 – 89 points
grade 2: 90 – 119 points
grade 3: 120 – 149 points
grade 4: 150 – 179 points
grade 5: 180 – 210 points.

Project work:
The students are required to work in the project a total of 135 hours.
- One working hour equals 1 point.
- Participating in one Tech Club session equals 2 points.
- Hosting one Tech Club session equals 5 points (this includes the time spent on planning the content and presenting).
- Participating to one ICT Guest Lecture equals 3 points.

The formative assessment of students' performance in the projects is based on self and peer assessment, customer’s feedback (if available) and project manager’s feedback.
All the required hours done equals to 135 points, every missing 15 hours means one grade point reduction of the grade student has received from the evaluation.

The final grade of the course is weighted average:
- Assignments and presence 50%
- Project work (evaluation based on self- and peer assessment) and project hours 50%

Accepted grade cannot be raised.

Assessment criteria, fail (0)

Less than 60 points from assignments, project working hours not completed.

No show, not carrying out responsibilities, disappearing from team work, lack of communication with other team members.

Student has to pass assignments and project work to complete the course.

Assessment criteria, satisfactory (1-2)

Grade 1: 60-89 points from assignments and attendance + completing project work hours.

Grade 2: 90-119 points from assignments and attendance + completing project work hours.

Poor, but satisfactory performance both in independent work and team work. Low participation on lectures and other activities.

Student has to pass assignments and project work to complete the course.

Assessment criteria, good (3-4)

Grade 3: 120-149 points from assignments and attendance + completing project work hours.

Grade 4: 150-179 points from assignments and attendance + completing project work hours.

Good performance both in team work and independent work. Active participation on lectures and other activities.

Student has to pass assignments and project work to complete the course.

Assessment criteria, excellent (5)

Grade 5: 180-210 point from assignments and attendance + completing project work hours.

Excellent performance both in team work and independent work. Active participation on lectures and other activities.

Student has to pass assignments and project work to complete the course.

Materials

All course materials and instructions can be found in It'sLearning workspace

Teaching methods

The course is implemented as face-to-face teaching using electronic work tools with a schedule according to the timetable. The course material is added to It'sLearning as the course progresses and is available to students until the end of the course. In some of the face to face meetings students are participating as users in real user tests of R&D projects of TUAS.

There are several individual exercises during the course related to the topics covered on the lectures.

During the course, a group exercise is carried out , where the things learned during the course are applied to a practical application. A report is produced from the exercise work, which is evaluated as part of the whole. The progress of the exercise is followed with pre-determined milestones.

Some Q&A sessions will be arranged where students can discuss and get a feedback from exercises done during the course.

Exam schedules

There are no exams or re-exam possibilities due to course implementation nature.

International connections

In the course, the basic skills of usability and usability planning are studied. The examples and tasks contain specific application examples. The study course uses source material in English, which gives students the ability to understand international engineering literature, publications, standards, etc. When solving assignments, students are encouraged to work in a team. Digital study material and an electronic learning environment are used in a variety of ways in the course. UX and UI designers' role in sustainable software engineering is discussed.


- Weekly face-to-face meetings with lecture teaching and small group work
- Learning by doing and experimenting (exercise tasks, project work, information search)
- Small group work and peer learning
- Self-study material
- Teacher guidance and examples

Completion alternatives

None

Student workload

Contact teaching and exercises 30h
Q&A sessions 6h
Personal studying, individual exercises and group work 94h

Content scheduling

• 9/24 : usability definition, benefits, principles and operating models
• 10/24 : human as user (participation in usability tests), interaction, culture and environment and usability evaluation
• 11/24: usability testing, user research, conceptual design and sense of sight and visual observation
• 9-12/24: practice work on the topics discussed in the course. It is carried out in small groups.

The content of the course is divided into three areas: analysis, planning and evaluation.
In the first part, the acquisition of user data is practiced as a basis for planning. In the second part, you practice creating an interactive user interface. In the third part, user interface and user experience evaluation methods are practiced.
- Basics of user orientation and usability
- User research and information acquisition methods
- Design sprints and creating an interactive user interface
- Usability assessment methods and tools
- Design and execution of usability tests

Further information

All course materials and instructions can be found in It'sLearning workspace.

Evaluation scale

H-5

Assessment methods and criteria

Individual exercises: Minimum to pass 50% of total points (max. points will be announced and published in the beginning of the course). Graded 0-5. 50% of total assessment. [summative assessment, teacher/automatic assessment]
Group exercise: Minimum to pass 50% of total points (max. points will be announced and published in the beginning of the course). Graded 0-5. 50% of total assessment. The task in small groups is project-based work. [summative assessment, teacher assessment]

Both individual and group exercise must be passed successfully to pass the course.

Minimum 50% attendance on the lectures is mandatory to pass the course. Higher attendance rewards with a bonus for total grade in following way:
Bonus for grade
50-60% 0,1
60-70% 0,2
70-80% 0,3
80-90% 0,4
90-100% 0,5

Assessment criteria, fail (0)

Student has not met the requirements to pass the course. 50% attendance, minimum 15 points from group exercise and minimum 15 points from individual exercises.

Assessment criteria, satisfactory (1-2)

The student knows the topics covered in the course and recognizes the practical design tasks to which they could be applied.

Assessment criteria, good (3-4)

The student is familiar with the topics covered in the course and knows how to use them in practical planning tasks.

Assessment criteria, excellent (5)

The student has mastered the topics covered in the course and knows how to apply them independently to practical design tasks.

Objective

After completing the course, the student will be able to:
- Understand agile utilization of interactive technologies, known from the entertainment industry, in different field of operation
- Understand the values of an attractive user interface design and positive user experience when using interactive technologies – such as virtual reality headsets, augmented reality devices and similar
- Critically evaluate and correct UX designs to suit the needs of target users
- Integrate sound UX principals into the application development for various interactive technologies
- Make use of the latest standards and tools for evaluating interactive technology UIs
- Develop appealing user interfaces (UI) for specific interactive technology applications
- Apply subjective analysis techniques for immersive sound validation

Content

- User interface design standards from latest academic literature
- User experience design standards from latest academic literature
- Principles of user-centred design and quick prototyping by using interactive UX solutions with certain novelty value for new applications
- UI development tools and evaluation metrics
- UX measurement approaches and methods
- Room acoustics, sound source identification and hearing

Materials

Unity Create with VR online material and material by TUAS. All necessary documentation and other material toward the successful completion of the Advanced UX and UI course will be shared with students throughout the course via Itslearning

Teaching methods

The course will be delivered through practical Game Lab work. Peer-assisted learning is required throughout the course.

The course material, assignments and direct instructions will be shared through Itslearning. Students will be granted access to the Teams page based on an active course registration in the Peppi system.

Mandatory participation for 70% of the close contact and laboratory sessions due to practical nature of the course and the need of XR-equipment and support.

Exam schedules

There are no exams for this course.

This course does not have any retake possibilities. Failing the course means that students will have to repeat it the following year.

International connections

This course leans on CDIO principles and takes a project-based learning approach.

Completion alternatives

Competence demonstration, if you have experience from industry or experience that is compatible with the course content contact the lecturer.

Student workload

This course requires students to work 135 hours and is divided as follows:
-Instructed sessions 36h
-Partly supervised laboratory work: 48 h
-Homework: 61 h
Course has individual work and 1 group assignments.

Group assignment:

- Instructor will introduce the topic, present the learning material and define the assignment deliverable;
- Student groups will be required to conduct independent preliminary research on the assignment topic;
- Student groups must familiarize themselves with the assignment technology.
- Student groups must conduct the work to complete the assignment deliverable.
- Assignment submissions will be demo presentation for 15 minute of the group’s assignment deliverable.

Content scheduling

1st Session
Course, Technology and assignment introductions.
Individual assignments
2nd Session
Students starts working with Unity Create With VR Material
5th Session
Student groups are formed and they start working with Mixed Reality Workshop
7h or 8th Session
Student groups starts working with XR-Project and complete assignment’s instructions
12th Session
Student groups present their XR-projects and course ends.

Further information

The practical elements of the course will be supported with the assistance of FIT-research group engineer who will also act as industry expert for evaluating group performance in the assignments.

The course material, assignments and direct instructions will be shared through Itslearning. Students will be granted access to the Itslearning based on an active course registration in the Peppi system.

Passing this course is a prerequisite for continuing with Serious Game Project Course and 4th-year studies – no exceptions will be made.

Evaluation scale

H-5

Assessment methods and criteria

Mandatory participation for 70% of the close contact and laboratory sessions.
The course consists of 1 group assignments.
- Group Assignment : Create an XR-project based on the instructions

The class will be divided into groups of 4-5 students each. - Each group will complete the assignment.

Student groups must submit all individual assignments and 1 group assignment to be eligible to pass the course - failure to submit an assignment will cause the entire group to fail the course. The group work will be assessed as peer evaluation.

The course is evaluated as follows:
- Individual assignment: Lecturer overall impression of assignment (H-5).
GROUP grade:
- Industry expert evaluation of each assignment (H-5);
- Lecturer overall impression of each assignment (H-5).
- Peer evaluation after each assignment (H-5).
The average of these gives a group grade for each student.

INDIVIDUAL student per group grade
Each student will also be measured on their contribution for the entire course. That is, at the end of the course each student in every group will be given the opportunity to conduct a self- and peer-evaluation of their individual team member performance and contribution for all 3 assignments. From this evaluation, each student will have a:
- Self assessment of the contribution made;
- Group member evaluation of the contribution made;
The average of these gives an individual grade for each student.

The final course grade for each student is calculated by:
(GROUP grade x 0,5) + (INDIVIDUAL grade x 0,5)

Based on peer feedback and course presenter observations, the lecturers may use their discretion to fail or lower the grade of individual students.

Passing this course is a prerequisite for continuing with Serious Game Project Course and 4th-year studies – no exceptions will be made.

Assessment criteria, fail (0)

Failure to submit individual assignment or the group assignment will cause the entire group to fail the course.
Individual non-participation as determined by the peer-evaluation will also lead to failing the course.
Failure to participate for 70% of the close contact and laboratory sessions.

Assessment criteria, satisfactory (1-2)

- Deliverable contains a few of the features outlined in the assignment
- Did not adequately apply preliminary research to complete the assignment
- Deliverable is incoherent or does not work

Assessment criteria, good (3-4)

- Deliverable contains most of the features outlined in the assignment
- Adequately applied preliminary research to complete the assignment, but lacking creativity
- Deliverable is coherent and functions as required by the assignment

Assessment criteria, excellent (5)

- Deliverable contains all the features outlined in the assignment
- Creatively applied preliminary research to complete the assignment
- Deliverable is coherent and exceeds the assignment requirements

Objective

After completing the course, the student can:
- work with advanced topics in data engineering and AI

Content

Advanced topics in Data Engineering, AI and data analytics such as
- application security
- data privacy
- legislation on data protection
- ethics of AI

Materials

Course materials are prepared by the lecturer from various sources including books, online material, etc.

Recommended books to study in this course are:
-- Practical Data Privacy: Enhancing Privacy and Security in Data 1st Edition by Katharine Jarmul
-- Fundamentals of Data Engineering: Plan and Build Robust Data Systems 1st Edition
by Joe Reis and Matt Housley

Teaching methods

Weekly contact sessions with total of 3 hours of theory and practical exercises.

Exam schedules

Exams including retake will be in Week 48 or 49 (at the same day as we have the regular lectures).

International connections

The course includes about 11 theory sessions and personal practice tasks.

This learning method combines theoretical knowledge with practical applications and real-world examples. It emphasizes understanding data engineering fundamental and privacy AI concepts, studying relevant technologies and techniques, and exploring practical implementations and use cases. Hands-on exercises, case studies, and projects will be incorporated to reinforce the learning experience

Completion alternatives

The exercises are mainly performed using Jupyter Notebook or other types of code scripts. Students will use TensorFlow and/or PyTorch. Strong python programming skills are needed to complete the exercises in part II.

Student workload

11 sessions (2.9-29.11.24 ) each 3 hours (2h lecture, 1h practice)+ Exam

Contact hours:
- Weeks 36 - 47: Theory & practice (3h/week): 11 x 3h = 33h
- Week 48: Exam: 2h
- In addition, about 5 support and inquiry hours (biweekly): 5x 1h = 5h

Total contact hours: 40 hours
Independent study and homework: about 90 h

Content scheduling

The course will be provided in two parts covering the following concepts:
Part I:
-- data security (encryption)
-- data privacy
-- data warehouses and data lakes
-- legislation on data protection (GDPR, data act)
Part II:
-- Data Regulations and Ethics in AI
-- Synthetic data generation
-- Differential privacy techniques
-- Decentralized machine learning and federated learning

Evaluation scale

H-5

Assessment methods and criteria

This course comprises 100 points including:
-- 22 points (1+1p each contact class: Lecture and Practical Session)
-- 44points for exercises
-- 34points for the exam

-Participation and exercises (50% of total to pass): Students must achieve at least 50% of the points to pass the course. Participation points can only be gained by being present in class during the Lecture and Practical sessions.

- Exam (50% of total points to pass): Students must achieve at least 50% of the points in order to pass the course.

The course is graded on a scale of 0-5.

Grading will be according to the total points collected by the student during the course as well as the exam.
1: 50% (minimum to pass the course)
2: 60-69%
3: 70-79%
4: 80-89%
5: 90-100%

Assessment criteria, fail (0)

<50% of total points or failed exam, exercise or participation points total.

Assessment criteria, satisfactory (1-2)

50-69% of the total points with passed exam, exercise and participation.

Assessment criteria, good (3-4)

70-89% of the total points with passed exam, exercise and participation.

Assessment criteria, excellent (5)

90-100% of the total points with passed exam, exercise and participation.

Objective

After completing the course the student can:
* program efficiently in a team
* reuse code and utilize libraries
* understand and apply some design patterns
* use an IDE as a programming tool
* use a version control system

Content

* relevant programming libraries
* learning some common design patterns
* using IDE in programming
* using a version control system in application development
* project work: implementing an application in a team

Materials

The course book:

Microservice APIs: Using Python, Flask, FastAPI, OpenAPI and more
Jose Haro Peralta
Mar 7, 2023

The part 3 of the course book "Designing And Building GraphQL APIs" is going to be totally skipped.

A limited number of book licenses is going to be available via TUAS' electronic library.

Other learning material can be announced during the course.

Teaching methods

- reading the course books and other reading material, watching videos
- participating in the lectures
- programming together with instructor
- programming alone
- defining interactive documents
- participating in the teamwork

Completion alternatives

The student can complete the course by demonstrating his knowledge and skills of the subjects of the course, for example with the work samples they have made. However, this must be agreed with the instructor during the first 4 weeks of the course.

The student can include a corresponding course taken elsewhere at some educational institution that is acceptable by our educational institution. This happens via AHOT process. Also this matter should be initiated immediately at the beginning of the course.

Student workload

30 h contact lessons
4 h presenting and following team works onsite
47 h preparing teamworks
54 h doing personal exercises

Content scheduling

The contents.

REST API
Microservice Architecture
Designing and implementing a back-end service with a REST API
Documenting a REST API
Testing the REST API
Using professional tools

The programming language is Python.

6 personal assignments.
Two teamworks (not compulsory)

Evaluation scale

H-5

Assessment methods and criteria

The maximum number of points available from course is 120.

Of that maximum, 60 points comes from 6 individual exercises, 40 points from teamworks, and 20 points from being present on the lectures.

The course evaluation scale is the following:

Min points -> Grade

0 -> 0
40 -> 1
56 -> 2
72 -> 3
88 -> 4
104 -> 5

An additional condition: You must to get at least 25 points from the exercises to pass the course.

The points from being present are calculated in a following way:

Percentage of being present on the normal lectures -> points

20% -> 5
40% ->10
60%->15
80%->20

Please also note that by being present you can earn some of the points available from the individual exercises working together with the instructor.

You must be present in demonstration. It does not accumulate your points of being present. If you are not present in the demonstrations, then there is a reduction of 50 % of the points of your returned exercises on these demos. There is also a reduction of 50 % for exercises that are returned late. No exercises are accepted after the end date of the course implementation. After the end date of the course, no substitute or supplementary assignments will be given either. The student must therefore make sure that he collects enough points from different performances during the time of the course.

Assessment criteria, fail (0)

The student has not managed to accumulate enough points to pass the course during the time of the course. Consequently, they have not been able to demonstrate the kind of competence on the basis of which an acceptable grade could be given.

Assessment criteria, satisfactory (1-2)

The student understands the basic of the REST API
The student knows what microservice architecture and microservices are
The student can implement a simple REST API and call the services it offers
The student understands the importance of documenting the REST API in a modern way
The student is ready to use the programming, documentation and testing tools necessary for API development

Assessment criteria, good (3-4)

The student understands the basics of the REST API and related authentication
The student knows what microservice architecture and microservices are
The student can implement a simple REST API, the related authentication and call the services it offers
The student understands the importance of REST API documentation in a modern way and knows how to prepare these documents
The student can use the programming, documentation and testing tools necessary for API development
The student knows how to work in a project where a microservice that permanently stores data is implemented

Assessment criteria, excellent (5)

The student understands the basics of the REST API and related authentication
The student knows what microservice architecture and microservices are
The student knows how to implement a simple REST API, the related authentication and call the services it offers
The student understands the importance of REST API documentation in a modern way and knows how to prepare these documents
The student can test the REST API
The student can use efficiently the programming, documentation and testing tools necessary for interface development
The student can effectively search for information to develop their skills and solve problems
The student can work proactively and efficiently in various roles in API programming projects
The student knows how to work in a project where a microservice that permanently stores data is implemented

Objective

After completing the course the student can:
* program efficiently in a team
* reuse code and utilize libraries
* understand and apply some design patterns
* use an IDE as a programming tool
* use a version control system

Content

* relevant programming libraries
* learning some common design patterns
* using IDE in programming
* using a version control system in application development
* project work: implementing an application in a team

Materials

Python Crash Course
3rd Edition
A Hands-On, Project-Based Introduction to Programming
Eric Matthes
January 10, 2023
ISBN-10 : 1718502702
ISBN-13 : 978-1718502703

The reading are will be concentrated mostly on chapters 9 and 18 - 20.

Please note that there is a limited number of the book's 3rd
editions available in eBook Central for you to read.

Some other material will be introduced during the course too.

Teaching methods

- reading the course books and other reading material, watching videos
- participating in the lectures
- programming together with instructor
- programming alone
- participating in the teamworks

Exam schedules

No exam

Completion alternatives

The student can complete the course by demonstrating his knowledge and skills of the subjects of the course, for example with the work samples they have made. However, this must be agreed with the instructor during the first 4 weeks of the course.

The student can include a corresponding course taken elsewhere at some educational institution that is acceptable by our educational institution. This happens via AHOT process. Also this matter should be initiated immediately at the beginning of the course.

Student workload

34 h contact lessons
12 h presenting and following team works
45 h preparing teamwork
44 h doing personal exercises

Content scheduling

During the course a web site will be created by using Python language and Django web application programming framework.

Professional tools like Git will be used. The site will follow the MVT version of the MVC architectural pattern.

The students will deepen their skills in the team works.

Onsite lessons. Theory lessons are for theory and presentations of theoretical team works. Practical lessons are for programming together. Demonstrations are for going through some of the solutions the students have done for the individual exercises.

7 personal assignments
2 team works (theory and programming works)

Evaluation scale

H-5

Assessment methods and criteria

The maximum number of points available from course is 120.

Of that maximum, 70 points comes from individual exercises, 30 points from teamwork, and 20 points from being present on the lectures.

The course evaluation scale is the following:

Min points -> Grade

0 -> 0
40 -> 1
56 -> 2
72 -> 3
88 -> 4
104 -> 5

Please note this additional condition: You must get at least 20 points from the exercises and 10 points from the teamworks to pass the course.

The points from being present are calculated using the following scale:

Percentage of being present on the normal lectures -> points

20% -> 5
40% ->10
60%->15
80%->20

Please also note that by being present you can earn some of the points available from the individual exercises working together with the instructor.

You must be present in demonstration. It does not accumulate your points of being present. If you are not present in the demonstrations, then there is a reduction of 50 % of the points of your returned exercises on these demos. There is also a reduction of 50 % for exercises that are returned late. No exercises are accepted after the end date of the course implementation. After the end date of the course, no substitute or supplementary assignments will be given either. The student must therefore make sure that he collects enough points from different performances during the time of the course.

Assessment criteria, fail (0)

The student has not managed to accumulate enough points to pass the course during the time of the course. Consequently, they have not been able to demonstrate the kind of competence on the basis of which an acceptable grade could be given.

Assessment criteria, satisfactory (1-2)

The student knows the possibilities of Python programming in web application development
The student understands what a web application framework is
The student understands web technologies and knows solutions and problems related to web applications
The student knows the MVT architectural model
The student knows what an ORM is
The student knows how template and template engine are related to user interfaces
The student knows what authentication and authorization are
The student is ready to implement a simple web application

Assessment criteria, good (3-4)

The student knows how to utilize the possibilities offered by Python programming in web application development
The student understands what a web application framework is
The student knows how to use web technologies and knows solutions and problems related to web applications
The student knows the MVT architecture model and knows how to program applications that follow it
The student knows what ORM is and knows how to use it for the permanent storage of web application data
The student knows how a template and a template engine are related to user interfaces and knows how to use them to build user interfaces in web applications
The student knows how to authenticate and authorize users in web applications
The student can implement a simple web application
The student is able to work on web application projects

Assessment criteria, excellent (5)

The student knows how to effectively utilize the opportunities offered by Python programming in web application development
The student understands what a web application framework is and can evaluate the consequences of its application
The student knows how to use web technologies and knows solutions and problems related to web applications extensively
The student knows how to search for and evaluate suitable solutions and tools and apply them to the problems they encounter
The student knows the MVT architecture model and knows how to program applications that follow it
The student knows what an ORM is and knows how to use it in a versatile manner in the permanent storage of web application data
The student knows how template and template engine are related to user interfaces and knows how to use them versatilely to build user interfaces in web applications
The student knows how to authenticate and authorize users in web applications
The student knows how to implement many kinds of web applications
The student is able to work in web application projects in various roles and to search for effective solutions to fulfill customer requirements

Objective

After completing the course the student can:
* program efficiently in a team
* reuse code and utilize libraries
* understand and apply some design patterns
* use an IDE as a programming tool
* use a version control system

Content

* relevant programming libraries
* learning some common design patterns
* using IDE in programming
* using a version control system in application development
* project work: implementing an application in a team

Materials

Opintojaksolla on käytössä oppikirja, mutta myös opettajan itse laatima materiaali, jonka varassa pärjännee ilman oppikirjaakin. Muita materiaaleja ovat tehtävänannot, jotka julkaistaan kurssin kuluessa.

Oppikirjan tiedot ovat seuraavat:
Python Crash Course
3rd Edition
A Hands-On, Project-Based Introduction to Programming
Eric Matthes
January 10, 2023
ISBN-10 : 1718502702
ISBN-13 : 978-1718502703

Kirjan 3. painos on luettavissa sähköisessä muodossa eBook Central -ympäristössämme.

Teaching methods

Oppimateriaalin lukeminen, ongelmanratkaisu kautta oppiminen, oppiminen käytännön ohjelmointitehtävien kautta tekemällä esimerkki- ja ongelmalähtöisesti, ryhmissä oppiminen, oppiminen ryhmätyötä tekemällä

Exam schedules

Opintojakson toteutuksella ei ole tenttiä.

International connections

Pedagogiikka noudattaa perinteistä opettajajohtoista menetelmää sekä aktiviteettiorientoitunutta tehtävien tekemistä ja luovaa ongelmanratkaisua. Kestävä kehitys huomioidaan käyttämällä olemassa olevaa infrastruktuuria lisärakentamisen tai laitehankintojen sijaan. Virtualisointia soveltamalla voidaan käyttää heterogeenista laitekantaa ilman tarvetta uusia laitteita. Opetus tapahtuu koulurakennuksessa, jossa opiskelijat ovat keskimäärin muutoinkin paljon, mikä vähentää matkustamista eri paikkojen välillä.

Completion alternatives

Opintojakso tarjotaan vain yhdessä muodossa, mutta huomioidaan tutkintosäännön asettamat mahdollisuudet.

Student workload

Oppitunnilla kuunteleminen ja seuraaminen, oppimateriaalin opiskelu, harjoitustehtävät, ryhmätyönä tehtävä harjoitustyö, yhteensä 135 tuntia

Content scheduling

Esitietovaatimukset: Ensimmäisen vuosikurssin opintojen oppisisältöjen hallinta tai vastaavat tiedot.

Sisältö:
Kurssin aikana rakennetaan verkkosivusto käyttäen Pythonia ja Django web-sovelluksen ohjelmointi-frameworkia. Verkkosivusto noudattaa erästä MVC-arkkitehtuuri-patternin versiota.

Opiskelijat harjoittelevat verkkosivuston tekoa syventäen osaamistaan tekemällä ryhmätyön.

Oppitunnit: Teoria, ohjelmointi yhdessä, demotehtävät ja ryhmätyö, joka voi koostua yhdestä tai kahdesta osiosta. Mahdolliset puhtaat teoriatunnit ja käytännön ohjelmointitunnit etenevät kurssin aikana rinta rinnan.

Oppitunteja tarjotaan 56 tuntia syyslukukauden kuluessa. Näistä puolet on kolmen ryhmän yhdistetylle ryhmälle ja puolet pienille ryhmille erikseen.

Further information

Opintojaksolla on käytössä suullinen viestintä oppitunneilla. Kirjallinen viestiminen toteutuu Itslearningin ja sähköpostin välityksellä.

Evaluation scale

H-5

Assessment methods and criteria

Tehtäväksi annetaan:
Arviolta 7 henkilökohtaista harjoitustehtäväkokonaisuutta: 70 pistettä max
Ryhmätyö: 30 pistettä max
Läsnäolo: 20 pistettä max

Tehtävät on palautettava erikseen annettuun aikarajaan mennessä, jotta niistä voi saada pisteitä. Aikarajan jälkeen palautetuista tehtävistä voi saada enintään puolet tavallisista maksimipisteistä. Opettaja voi huomauttaa kurssin alkupuolella opiskelijalle, jos näyttää siltä, ettei opiskelijan nykyaktiivisuus opintojaksolla ennusta hyväksyttyä suoritusta. Kaikki opintojakson osasuoritukset on palautettava kuitenkin opintojakson meneillään olevan toteutuksen kuluessa silloinkin, kun niitä palautetaan myöhässä.

(i) Opiskelijan on saatava vähintään 10 pistettä ryhmätyöstä saadakseen hyväksytyn arvosanan opintojaksosta.

(ii) Opiskelijan on saatava yhteensä vähintään 40 pistettä henkilökohtaisista tehtävistä ja ryhmätyöstä saadakseen hyväksytyn arvosanan opintojaksosta.

(iii) Opiskelija voi saada alimpaan arvosaan oikeuttaviin pisteisiin arvosanaa korottavia pisteitä kaikista kolmesta pistelähteestä, joita ovat siis harjoitustyö, viikoittaiset tehtävät sekä läsnäolo.

Läsnäolot kerätään paperiseen rastilistaan, joka kiertää oppitunnilla luokassa. Näistä lasketaan kokonaisläsnäolon suhde, jonka mukaan saadaan ansaittu osuus 20 läsnäolopisteestä. Läsnäolopisteet annetaan seuraavan skaalan perusteella:

Läsnäoloprosentti käytännön- ja teorialuennoilla -> pisteitä:

alle 20% -> 0
20% -> 5
40% ->10
60%->15
80%->20

Arviointiasteikko (pisteet --> arvosana):

alle 40 -> 0
40 -> 1
56 -> 2
72 -> 3
88 -> 4
104 -> 5

Assessment criteria, fail (0)

Opiskelija ei ole palauttanut riittävästi pyydettyjä tehtävien oikeaksi arvioitavissa olevia ratkaisuja kurssilla määritellyillä tavoilla annettuihin aikarajoihin mennessä tai ei osaa uskottavasti ja osaamista osoittavalla tavalla tehdä selkoa palauttamistaan ratkaisuista sekä pyydettäessä demota laatimiaan ratkaisuja, luomiaan järjestelmiä tai vastata opettajan esittämiin kysymyksiin, jotka koskevat tehtävien ratkaisuja, kurssin keskeisiä oppeja ja opittaviksi asetettuja periaatteita, näiden oppien soveltamista tai käytännön menetelmiä. Kysymyksiin vastaamisella tarkoitetaan joko välitöntä suullista vastaamista tai valvottua kirjallisen vastauksen laatimista opettajan määräämästä tavasta riippuen tai muuta erikseen tilannetta varten määriteltyä ja tarpeelliseksi perustelvissa olevaa tapaa. Demoamisella tarkoitetaan kurssilla määritellyn tekniikan varassa suoritettua itse kirjoitetun ohjelmallisen ratkaisun tai useista sellaisista muodostuvien kokonaisuuksien toimintaan saattamista valvotusti ja tapahtumia selostaen. Vilppi tai muu perusteltu selvästi hylkäykseen johtava seikka voi myös aiheuttaa hylkäyksen.

Assessment criteria, satisfactory (1-2)

Opiskelija osaa opintojakson sisällön keskeisimmät periaatteet ja opit sekä osaa rakentaa Djangolla opintojaksolla käytössä olevaan ympäristöön tehtävänannossa pyydetyn järjestelmän, joka soveltaen mukailee opintojakson pääopintomateriaalissa esitettyä järjestelmää kaikkine toiminnallisuusosioineen, mutta esitettyä laajuutta suppeammin. Osaaminen osoitetaan lisäksi tehtävien hallinnalla ja kurssin oppitunteihin osallistumalla ja niissä aktiivisesti kuuntelemalla ja annettuja tehtäviä tekemällä annetun pisteintervallin arvoisesti.

Assessment criteria, good (3-4)

Opiskelija osaa opintojakson sisällön keskeisimmät periaatteet ja opit sekä osaa rakentaa Djangolla opintojaksolla käytössä olevaan ympäristöön tehtävänannossa pyydetyn järjestelmän, joka laajasti soveltaen mukailee opintojakson pääopintomateriaalissa esitettyä järjestelmää kaikkine toiminnallisuusosioineen. Osaaminen osoitetaan lisäksi tehtävien hallinnalla ja kurssin oppitunteihin osallistumalla ja niissä aktiivisesti kuuntelemalla ja annettuja tehtäviä tekemällä annetun pisteintervallin arvoisesti.

Assessment criteria, excellent (5)

Opiskelija osaa opintojakson sisällön keskeisimmät periaatteet ja opit sekä osaa rakentaa Djangolla opintojaksolla käytössä olevaan ympäristöön tehtävänannossa pyydetyn järjestelmän, joka laajasti soveltaen mukailee opintojakson pääopintomateriaalissa esitettyä järjestelmää kaikkine toiminnallisuusosioineen ja osin ylittää oppimateriaalissa esitetyn perusversion monipuolisuudellaan. Osaaminen osoitetaan lisäksi tehtävien hallinnalla ja kurssin oppitunteihin osallistumalla ja niissä aktiivisesti kuuntelemalla ja annettuja tehtäviä tekemällä annetun pisteintervallin arvoisesti.

Objective

After completing the course, the student can:
- describe what kind of AI applications are available
- describe how AI based applications can be developed
- develop applications using AI

Content

Actual content is decided during the course implementation phase.
The contents vary every year.

Materials

Material available via the learning environment (ITS).

Teaching methods

The course includes about 12 theory sessions and personal practice tasks (3h),

There will be also quest lecturers (from companies or RDI people)

Exam schedules

No exam or in week 17.

International connections

This learning method combines theoretical knowledge with practical applications and real-world examples.
Weekly assignments based on the topics covered.
Around half of the exercises are done during the contact hours.
Additionally, exercises for home work.

Additionally:
- Mid-term project: Develop a simple AI application
- Final project/exam: Comprehensive AI application using multiple techniques learned in the course

Completion alternatives

None.

Student workload

Contact hours:
- Week 3: Course Introduction 2h
- Weeks 4 - 16: Theory & practice (3h/week): 12 x 3h = 36h
- Week 17: Exam/Finals 2h
Total contact hours: 40 hours

Independent study and homework: about 90 h

Total: approximately: 130 hours

Content scheduling

Weekly time schedule plan
3. Introduction to Course and AI-based applications & Examples of AI-Based Applications in various industries
4. Steps to develop AI Applications with a help of tools and frameworks
5. Data-Driven AI and techniques for data-driven AI development
6. Use of Open Data and building Decision Trees with it
7. Handling and processing tabular data and applications of tabular data
9. Generative AI and applications of generative AI (e.g., art, music, text generation)
10. Language Models (e.g., GPT, BERT) and NLP applications NLP
11. Computer Vison and it's real-world applications (e.g., facial recognition, autonomous vehicles)
12. Object Recognition and techniques & applications for object recognition
13. Synthetic Data and use cases of it.
14. Optimization in AI and applications of optimization in AI models
15. IBM Watson and practical applications with it (e.g. image recognition, NLP)
16. Building and training models using PyTorch & TensorFlow
17. Exam/Presentation of final project results
+ projects to build an AI application during the course (one alone and another in team)

Further information

ItsLearning

Evaluation scale

H-5

Assessment methods and criteria

You can achieve points from participation, exercises, participation and exam/final project:
- 20% points from participation
- 50% points from practical exercises in class room and home work
- 30% points from the final project work/exam

Objective

After completing the course the student:
- understands what the artificial intelligence is in social and health care
- can explain the basic concepts of artificial intelligence
- knows the available artificial intelligence applications in social and health care
- understands the possibilities and limitations of artificial intelligence in social and health care

Content

- Basics of Artificial Intelligence
- Artificial Intelligence Applications
- Neural networks
- Machine learning

Materials

The lecture material is mainly in English.

Lecture materials, exercises, and other resources will be distributed via ITS-learning.

Teaching methods

Lectures, code examples, and independent exercises

Exam schedules

The course exam can be retaken three times.

International connections

The course includes approximately 13 lectures or practice sessions.

Student workload

Contact hours in total: approximately 40 hours

Independent study and homework: 90 hours

Total: approximately 130 hours

Content scheduling

Starting from week 3 and continuing weekly

The course covers the following topics:

Basics and fundamental concepts of artificial intelligence
Traditional programming vs. machine learning
Regression and classification
Principles of neural networks
Data and its characteristics in machine learning
Supervised and unsupervised machine learning methods and applications
Backpropagation algorithm
Functioning of the perceptron algorithm
Reinforcement learning methods and applications
Deep learning methods and applications
Decision trees
Applications of generative artificial intelligence
Production and characteristics of synthetic data

Further information

Course announcements will be made via ITS-learning

Evaluation scale

H-5

Assessment methods and criteria

Assessment is on a scale of 0 to 5.

To pass the course, you must successfully complete the exam. The passing threshold for the exam is at least 40% of the maximum points. The passing grades are evenly distributed between 40% and 100%.

It is possible to earn additional points from exercises, which are added to the points from the passed exam. The points earned from exercises can raise the final grade by a maximum of 0.75.

Objective

After completing the course the student can:
Knows the main alternatives technologies on the server-side in developing web applications.
Masters one server-side scripting language and can use some important libraries.
Understands the basics of web application architectures.
Can use a content management system or an application framework in implementing a web application.
Can use efficient tools in server-side scripting.

Content

Learning a server-side scripting language.
Introduction to web application architectures.
Integrating a database server to a web application.
Using a content management system or an application framework in implementing a web application.
Tools for server-side scripting.
Implementing a small scale web application.

Materials

* Coursebook:
Get Programming with Node.js
Jon Wexler
Manning Publications
1 edition (March 15, 2019)

* The book is 480 pages, but the reading area of the course is less than 300 pages.

* Unfortunately, the book is not available in electronic form through the library of our educational institution.

Teaching methods

- Programming By doing learning
- Interaction with teacher and classmates
- Teamwork project

International connections

The course includes approximately 12 theory sessions and practice sessions where students work with practical tasks.

Additionally, there are 5 x 1h online Q&A sessions for extra support.

Furthermore, exercises for home work that will be partly demonstrated in during contact sessions.

A teamwork project will be introduced in the second month, requiring students to apply their teamwork skills and knowledge gained from the course to implement their final project

We may also utilize a flipped-classroom model for some lectures, where students will study the theoretical part at home and engage in practical implementation and discussions during class.

Student workload

- 12 times 3h theory and practice: 12 x 3h = 36h
- 5 times 1h online Q&A sessions = 5h
- Home and independent work: approximately 70h
- Teamwork final project: approximately 24h

Total: approximately 135 hours

Content scheduling

The course includes approximately 12 supervised work and theory sessions.
Additionally, 10 personal exercises for homework that will be partly demonstrate in during contact session.
Furthermore, the course has a teamwork project that must be done in a group of 4 students.

* Exercise work is done individually outside the instructional sessions. The topic of the assignment is specified during the first month of the course.

* Planned course progress: (preplan)
Content and topic of lectures. We proceed according to the some chapters in the coursebook.
Note: students will also have some independent study or self-study tasks from the book chapters.

1: Chapters 0-2 of the Course Start Theory and Development Environment Creation Book
2: Modules and a simple web server - chapters 3-4 of the book
3. Chapters 5 and 6 of the Request Processing and Routing Book
4: Chapters 8 and 9 of the Express and MVC book
5: Outlook and Error Handling - Chapters 10 and 11
6: MongoDB Database Connection and Mongoose Schemas and Templates - Chapters 13 and 14 of the book
7: Controllers and Models - Chapter 16 of the book
8: Working with Data Models - Chapters 17 and 18 of the book
9: Working with Data Models - Chapters 19 and 21
10: Sessions and User Authentication - Book Chapters 22-24

* Two lectures will be used for demo and other as yet undefined purposes.

* Each group must set aside 15 minutes for the last week of the course to demonstrate the assignment. Individual teamwork must also be able to demonstrate on this occasion.

* The study plan may change as the course progresses.

Further information

** Prerequisites for Back- End Development Course:
1- JavaScript: Basic Syntax and Control Structures, Functions and Scope, Asynchronous Programming

2- Databases

** Recommendations (Optional but Beneficial):
1- Basic Understanding of RESTful APIs: Knowledge of HTTP methods (GET, POST, PUT, DELETE) and status codes.

2- Experience with JSON: Understanding of JSON format for data interchange.

3- Basic Knowledge of Git: Familiarity with version control using Git.

Evaluation scale

H-5

Assessment methods and criteria

- The course is graded on a scale of 0-5.
*
- In order to pass the course, the student must earn at least 50% of the points of personal assignments and 50% of the points of Teamwork project.
*
- You can get a maximum of 10 points for each practice task. You can therefore get a maximum of 100 points for all practice tasks, which affect the evaluation by 3 units.
- Participation in group work: 0.0 - 2.0 units.
*
-Students can earn one extra unit (ECTS) if they participate on at least 9 sessions (2-3h per each session) of the course.
Note: Grades will be rounded down if they include decimals less than 0.5; otherwise, they will be rounded up. (e.g., 3.4 is rounded down to 3.0, but 3.5 or higher is rounded up to 4.0)

Assessment criteria, fail (0)

The student does NOT get at least 50% of the points in project OR did not get at least 50% of the points in the course exercises.

Assessment criteria, satisfactory (1-2)

The student got 40-59% of the points for the exercises in the course AND got a grade of 1 - 3 for the project work.

Assessment criteria, good (3-4)

The student got 40-59% of the points for the exercises in the course AND got a grade of 1 - 3 for the project work.

Assessment criteria, excellent (5)

The student got at least 85% of the points for the exercises in the course AND got a grade 5 for the project work.

Objective

After completing the course the student:
Knows the main alternatives technologies on the server-side in developing web applications.
Masters one server-side scripting language and can use some important libraries.
Understands the basics of web application architectures.
Can use a content management system or an application framework in implementing a web application.
Can use efficient tools in server-side scripting.

Content

Learning a server-side scripting language.
Introduction to web application architectures.
Integrating a database server to a web application.
Using a content management system or an application framework in implementing a web application.
Tools for server-side scripting.
Implementing a small scale web application.

Materials

The course books are

Get Programming with Node.js
Jon Wexler
Manning Publications
1st edition (March 15, 2019)

This book is unfortunately not available via TUAS (TuAMK) as ebook. There are few printed copies in out library.

The book is also already quite old, so that we need to modify some code and solutions during the course. However, the book is otherwise very good for being a course book.

Node.js for Beginners: A comprehensive guide to building efficient, full-featured web applications with Node.js
Ulises Gascón
Packt
May 2024

Other material will be announced during the course

Teaching methods

- reading the course books and other reading material
- participating in the lectures
- programming together with instructor
- programming alone
- participating in the teamwork

Exam schedules

No exam.

Completion alternatives

The student can complete the course by demonstrating his knowledge and skills of the subjects of the course, for example with the work samples they have made. However, this must be agreed with the instructor during the first 4 weeks of the course.

The student can include a corresponding course taken elsewhere at some educational institution that is acceptable by our educational institution. This happens via AHOT process. Also this matter should be initiated immediately at the beginning of the course.

Student workload

45 h contact lessons (Each 3h = 2h learning and 1h individual working with the presence of the instructor)
4 h presenting and following team works
40 h preparing teamwork
54 h doing personal exercises

Content scheduling

The course builds on 15 supervised lessons, 7 personal exercises each having multiple tasks, and a teamwork.
*
The teamwork is done in groups of 3 to 4 students. The teamwork commission is published in the middle of the course.
*
The planned course content:
*
Course introduction and the creation of the development environment
Node.js
NPM
ES6 modules
Express Web Framework and the MVC
Routing and handling http requests
Views and Templates
Error handling
Controllers
Models
CRUD and Data persistence
User sessions and authentication
Login and logout
Authorization
*
Three lessons are used for demos.
*
The teamwork is evaluated in an 15 minutes long evaluation event where the group presents its application to the instructor. Each member must clarify his or her input to the result. The source code must be presented too.

Evaluation scale

H-5

Assessment methods and criteria

The maximum number of points available from course is 120.

Of that maximum, 70 points comes from individual exercises, 30 points from teamwork, and 20 points from being present on the lectures.

The course evaluation scale is the following:

Min points -> Grade

0 -> 0
40 -> 1
56 -> 2
72 -> 3
88 -> 4
104 -> 5

Please note this additional condition: You must get at least 20 points from the exercises and 10 points from the teamwork to pass the course.

The points from being present are calculated using the following scale:

Percentage of being present on the normal lectures -> points

20% -> 5
40% ->10
60%->15
80%->20

Please also note that by being present you can earn some of the points available from the individual exercises working together with the instructor.

You must be present in demonstration. It does not accumulate your points of being present. If you are not present in the demonstrations, then there is a reduction of 25 % of the points of your returned exercises on these demos. There is also a reduction of 25 % for exercises that are returned late. No exercises are accepted after the end date of the course implementation. After the end date of the course, no substitute or supplementary assignments will be given either. The student must therefore make sure that he collects enough points from different performances during the time of the course.

Assessment criteria, fail (0)

The student has not managed to accumulate enough points to pass the course during the time of the course. Consequently, they have not been able to demonstrate the kind of competence on the basis of which an acceptable grade could be given.

Assessment criteria, satisfactory (1-2)

The student knows the operating principles and application areas of the Node.js runtime environment
The student knows how configuration files can be utilized in the development and deployment of web applications
The student knows the key issues related to the development of Web applications
The student knows what a web application framework is
The student knows the basic principles of the MVC architecture model
The student knows some of the key program libraries needed for programming web applications
The student knows how to use development tools suitable for tasks
The student knows how to program a simple dynamic website using the web application framework

Assessment criteria, good (3-4)

The student knows the operating principles and application areas of the Node.js runtime environment
The student knows how configuration files can be utilized in the development and deployment of web applications
The student knows the key issues and questions related to the development of Web applications and knows how to implement related solutions
The student knows how to use the web application framework
The student masters the basic principles of the MVC architecture model and knows how to implement them in practice
The student can use software libraries that are needed for programming web applications
The student knows how to use tools suitable for tasks
The student knows how to program a dynamic website using the web application framework
The student can implement user authentication, sessions and permanent storage
The student is well prepared to participate in a project developing a web application.

Assessment criteria, excellent (5)

The student knows the operating principles and the application areas of the Node.js runtime environment and can evaluate its suitability for the task
The student knows how to use configuration files in the development and implementation of web applications
The student masters the key principles and questions related to the development of Web applications and knows how to implement and evaluate related solutions
The student knows how to use the web application framework effectively and evaluate its suitability for the task
The student masters the basic principles of the MVC architecture model and knows how to implement it in practice
The student can evaluate and effectively use the program libraries needed for programming web applications
The student knows how to effectively use the tools suitable for the tasks
The student knows how to program a dynamic website using the web application framework
The student knows how to design and program a dynamic website with user authentication, sessions and permanent storage
The student is excellently prepared to participate in a project developing a web application.

Objective

After completing the course the student can:
- Describe how data can be managed and processed
- Describe how data can be stored in various places and formats
- Manage and analyze data with suitable tools
- Utilize data management tools to process data
- Understand and describe how mathematics can be used for data management

Content

Introduction to data management
Data storage formats
Data storage
Introduction to data processing
Linear algebra
Data management tools

Materials

Material available via the learning environment (ITS).

Teaching methods

Weekly contact sessions when 3 hours for theory and practical exercises.

Exam schedules

Exam in Week 49.
Retake exam in January 2025.

International connections

The course includes approximately 12 theory sessions and guided exercises sessions where students work with practical tasks.
Around half of the exercises are done during the contact hours.
Additionally, exercises for home work that will be partly demonstrated in during contact sessions.

Student workload

Contact hours
- 12 times 1h theory: 12 x 1h = 12 hours (groups together)
- 12 times 2h practice: 12 x 2h = 24 hours (in own group)
- Exam: 2 hours
- 1h Q&A sessions 5-6 times = 5 hours
TOTAL: 43 hours

Home and independent work: approximately 90 hours

Total: approximately: 130 hours

Content scheduling

Weeks 36 - 48:
Introduction to data management
Introduction to Jupyter Notebook
Data storage formats
Basics of linear algebra (vectors, matrices, linear equations)
Data processing and visualization with Python
Basics of virtualization and Linux shell commands
Introduction to databases
Recap
Week 49: Exam
Week 49: Exam

Further information

Additional information is share via ITS

Evaluation scale

H-5

Assessment methods and criteria

You can achieve points from participation, exercises, participation and exam:
- 20% points from participation
- 50% points from practical exercises in class room and home work
- 30% points from the exam

Assessment:
- Participation and exercise (50% of total to pass): Students must achieve at least 50% of the points to pass the course.
- Exam (50% of total points to pass): Students must achieve at least 50% of the points in order to pass the course.

The course is graded on a scale of 0-5.
Grading will be according to the total points collected by the student during the course as well as the exam.
1: 50% (minimum to pass the course)
2: 60-70%
3: 70-80%
4: 80-90%
5: 90- 100%

Assessment criteria, fail (0)

Less than 50% points

Assessment criteria, satisfactory (1-2)

50 - 69% points

Assessment criteria, good (3-4)

70 - 89% points

Assessment criteria, excellent (5)

At least 90% points

Objective

After completing the course the student:
- Knows different types of business information systems
- Understands the relationship between business and information systems
- Understands benefits and challenges related to information system integration
- Knows the main concepts and principles of ERP systems
- Can use an ERP system
- Can participate in ERP and IS procurement projects

Content

- Introduction to business information systems
- Introduction to ERP systems
- Using an ERP system in practise
- IS procurement process, tasks and documents

Materials

SAP UA:n SAP S/4HANA reading material and a case study. Available in digital form through the course environment.

The Odoo part uses a few chapters from the book:


Learn Odoo 12
Author: Greg Moss
Pages: 488 Size:
Publisher: Packt Publishing
Published: 31 October, 2019
eISBN-13: 9781789531480

The book is available in electronic form from our Ebook Central library.

Other material given by the instructors during the course, especially related to system procurement and development.

Teaching methods

Doing practical exercises and theory exercises in the classroom and at home.
Attending lectures
Working in groups
Reading literature and materials

Exam schedules

Exam in the last week of the course

International connections

The course introduces sustainable development related to the acquisition of an information system.

Completion alternatives

Not available

Student workload

Doing practical exercises and theory exercises in the classroom and at home 40 t
Attending lectures 40 t
Working in groups 40 t
Reading literature and materials 20 t

Content scheduling

Course contents in chronological order:
Basics of ERP systems 3 hours
Training of the use of the SAP ERP system 4h+2h
Purchasing an information system (preparing a tender request) 10h
Making an information system quotation 6h
Deploying and customizing Odoo ERP system 4h
Exam and presentation of exercises 4h

Further information

The teaching environment of the course with information and materials is itsLearning.
Applications such as Odoo and SAP are used during the course.

Teaching is carried out on site on campus. Practical ERP exercises (SAP and Odoo) require attendance in the classroom. The practice work is done in a small group and also requires attendance on the lessons on site.

Evaluation scale

H-5

Assessment methods and criteria

The course is graded as follows:

ERP: personal practice and theory exercises 30 p
Various information systems assignment 10 p
IT customer part of teamwork 20 p
IT supplier part of teamwork 20 p
Exam 20 p

A total of 100 p

Grade scale:

30 points -> grade 1; points 45 -> grade 2; points 60 -> grade 3; points 75 -> grade 4; 90 points -> grade 5.

Prerequisite: the student's points must be at least 10 points from Group work.

Assessment criteria, fail (0)

The student has not managed to accumulate enough points to pass the course during the time of the course. Consequently, they have not been able to demonstrate the kind of competence on the basis of which an acceptable grade could be given.

Assessment criteria, satisfactory (1-2)

The student knows what an enterprise resource planning system is and understands its importance in business
The student knows what a business process is
The student knows the concepts master data and a transaction
The student understands the stages of acquiring information systems and knows how to act in them.

Assessment criteria, good (3-4)

The student knows what an enterprise resource planning system is and understands its importance in business
The student knows the possible benefits and problems of enterprise resource planning systems
The student knows what a business process is and how an enterprise resource planning system can support its execution
The student knows the concepts master data, transaction, and their characteristics
The student knows the questions related to the selection and deployment of an enterprise resource planning system
The student has an understanding of why enterprise resource planning systems are often customized
The student has experience using an enterprise resource planning system
The student knows how to describe the operating environment and processes as required by the information system procurement, prepare prioritized system requirements and understand the evaluation criteria for tenders

Assessment criteria, excellent (5)

The student knows what an enterprise resource planning system is and understands its importance in business
The student knows the possible benefits and problems of enterprise resource planning systems
The student knows what a business process is and how an enterprise resource planning system can support its execution
The student knows the concepts master data, transaction, and their characteristics
The student knows the questions related to the selection and deployment of an enterprise resource planning system
The student has an understanding of why enterprise resource planning systems are often customized
The student has experience using an enterprise resource planning system
The student has experience in deploying and customizing an enterprise resource planning system in a small-scale
The student knows how to prepare comprehensive system requirements and justified tender comparison criteria, as well as utilize other quality-enhancing elements, such as sustainable development criteria, in the request for tenders.
The student knows how to communicate with the customer about the request for a quote and prepare a tender document and a demo implementation that meet the customer's requirements.

Objective

After completing the course the student can
- use derivatives to analyze functions
- use differentials to approximate changes and errors
- use integrals to calculate e.g. areas and volumes, mean values and square mean values
- solve integrable and 1. order separable differential equations
- use relevant mathematical denotation correctly

Content

- Limits
- The derivative
- Differentials
- Antiderivatives and the definite integral
- Applications of differentiation and integration
- On differential equations

Materials

Kirja: Tuomenlehto, Holmlund et al.: Insinöörin matematiikka. Edita 2018.
Itslearningin kautta jaettava muu materiaali.

Teaching methods

lähiopetus, tehtäväperustaisuus, itsenäinen opiskelu

Exam schedules

Osakokeet 3 kpl luentoaikoina, tarkemmat ajankohdat ilmoitetaan kurssin aikana Itslearningissä. Tarvittaessa järjestetään uusintatentti.

International connections

Opintojaksolla opiskellaan matemaattisia perustaitoja, jotka ovat insinöörityön perusta.

Completion alternatives

Kotitehtävät ja osakokeet (tai kurssin jälkeinen uusintatentti)

Student workload

Lähiopetusta n. 85 h.
Itsenäistä työskentelyä (opiskelumateriaali, tehtävät, osakokeisiin valmistautuminen) 50 h.
Yhteensä 135 h.

Content scheduling

- Raja-arvo
- Derivaatta
- Differentiaali
- Määräämätön ja määrätty integraali
- Differentiaali- ja integraalilaskennan sovelluksia
- Differentiaaliyhtälöistä

2x2h luento + 2h laskuharjoitus viikottain, 14 viikkoa

Further information

Edeltävyysehdot: Insinöörimatematiikan perusteet tai vastaavat tiedot ja taidot

Evaluation scale

H-5

Assessment methods and criteria

Arvosana perustuu osakokeiden pistemääriin sekä tehtyihin kotitehtäviin ja lähiopetukseen osallistumiseen.

Kurssin hyväksytyn läpäisemisen minimi vaatimus on yksi kolmasosa kurssin osakokeiden kokonaispistemäärästä (33%).

Arvosanaan vaikuttavat myös tehtyjen kotitehtävien palautus prosentti, sekä lähiopetukseen osallistumisaktiivisuus.

Assessment criteria, fail (0)

Opiskelija ei ole osoittanut saavuttaneensa opintojakson tavoitteita. Opiskelija tunnistaa ja osaa käyttää vain muutamia opintojakson aihepiirin käsitteitä eikä osaa soveltaa oppimaansa.

Hylätty arvosana seuraa, jos opiskelija ei ole suorittanut hyväksytysti välikokeita (alle 33 % osakokeiden kokonaispistemäärästä)

Opintojakso hylätään myös, jos opiskelijan suorituksissa havaitaan vilppiä. Ensimmäinen havaittu vilppi tai vilpin yritys johtaa yksittäisen koe- tai tehtäväsuorituksen hylkäämiseen. Toinen havaittu kerta johtaa koko opintojaksosuorituksen hylkäämiseen.

Assessment criteria, satisfactory (1-2)

Opiskelija on osoittanut saavuttaneensa opintojakson tavoitteet tyydyttävästi. Opiskelija tunnistaa ja osaa jossain määrin hyödyntää opintojakson aihepiirin käsitteitä.

Assessment criteria, good (3-4)

Opiskelija on osoittanut saavuttaneensa opintojakson tavoitteet hyvin, vaikka tiedoissa ja taidoissa onkin joillain osa-alueilla vielä kehitettävää. Opiskelija osaa käyttää hyvin opintojakson aihepiirin käsitteitä ja soveltaa oppimaansa opiskelun ja työelämän tilanteissa

Assessment criteria, excellent (5)

Opiskelija on osoittanut saavuttaneensa opintojakson tavoitteet kiitettävästi. Opiskelija hallitsee kiitettävästi opintojakson aihepiirin käsitteet ja osaa analysoida aihepiiriin liittyviä asioita sujuvasti ja perustellusti. Opiskelijalla on hyvät valmiudet soveltaa oppimaansa opiskelun ja työelämän tilanteissa.

Qualifications

Precalculus course or equivalent skills

Objective

After completing the course the student can
- use derivatives to analyze functions
- use differentials to approximate changes and errors
- use integrals to calculate e.g. areas and volumes, mean values and square mean values
- solve integrable and 1. order separable differential equations
- use relevant mathematical denotation correctly

Content

- Limits
- The derivative
- Differentials
- Antiderivatives and the definite integral
- Applications of differentiation and integration
- On differential equations

Materials

ITSL-alustalta löytyvä luento- ja tehtävämateriaali.

Teaching methods

Lähiopetus-luennot.
Tehtävien tekeminen yksin ja ryhmässä.
Itsenäinen opiskelu.
Kokeet.

Exam schedules

Kaksi osakoetta.
OSAKOE1 on puolessa välissä kurssia oppituntien 1-12 jälkeen. Yksi uusinta.
OSAKOE2 on kurssin lopussa oppituntien 13-22 jälkeen. Yksi uusinta.
Kurssin päätyttyä kummankin osakokeen voi uusia vielä yhden kerran.

Completion alternatives

-

Student workload

Luennot & laskuharjoitukset 22*3h.
Kokeet 2*2h.
Loput opiskelijan itsenäistä opiskelua ja laskutehtävien tekemistä.

Content scheduling

Differentiaalilaskenta, 6 ensimmäistä viikkoa:
1 Muutosnopeus
2 Raja-arvo
3 Derivaatan määritelmä
4 Polynomin derivointi
5 Funktion kulkukaavio
6 Derivaattafunktion kuvaaja
7 Derivointikaavoja
8 Yhdistetyn funktion derivointi
9 Potenssin derivointi
10 Eksponentin ja logaritmin derivointi
11 Derivointimenetelmiä
12 Differentiaali

Integraalilaskenta, 5 seuraavaa viikkoa:
13 Integraalifunktio
14 Integrointikaavoja
15 Yhdistetyn funktion integrointi
16 Määrätty integraali
17 Määrätyn integraalin ominaisuuksia
18 Pinta-ala
19 Tilavuus
20 Funktion keskiarvot
21 Integroituva differentiaaliyhtälö
22 Separoituva differentiaaliyhtälö

Further information

Sähköposti.

Evaluation scale

H-5

Assessment methods and criteria

Arvosana määräytyy osakokeista saadun yhteispistemäärän (max. 20+20=40) ja laskutehtävistä saadun pistemäärän (max. 10) perusteella seuraavan taulukon mukaisesti (osakokeista täytyy saada yhteensä vähintään 16 pistettä päästäkseen läpi kurssista):

Yhteispistemäärä Arvosana
0-15: 0
16-22: 1
23-29: 2
30-35: 3
36-42: 4
43-50: 5

Assessment criteria, fail (0)

Arvosanataulukon mukaan.

Assessment criteria, satisfactory (1-2)

Arvosanataulukon mukaan.

Assessment criteria, good (3-4)

Arvosanataulukon mukaan.

Assessment criteria, excellent (5)

Arvosanataulukon mukaan.

Qualifications

Precalculus course or equivalent skills

Objective

After completing the course, the student can:
- Describe what Cloud Services are, how they affect business and which new opportunities it may enable.
- Describe use cases and benefits of cloud services,
- Describe SAAS, PAAS, IAAS.
- Develop a solution that utilizes cloud services.

Content

Introduction to cloud services
Software as a service (SAAS)
Platform as a service (PAAS)
Infrastructure as a service (IAAS)
Virtual machines and containers
Security of cloud services
Project work

Materials

Task-specific material to be announced separately in Its Learning and in AWS academy.

Teaching methods

- Weekly face-to-face meetings with lecture teaching and small group work
- Learning by doing and experimenting (exercise tasks, project work, information search)
- Small group work and peer learning
- Self-study material
- Teacher guidance and examples

Exam schedules

No exam, and retake not possible after evaluation grade is published.

International connections

FLIP classrooms and learning by doing

Completion alternatives

Not possible

Student workload

Contact hours
- Course introduction: 3 hours
- 12 times 3h theory and AWS support: 12 x 3h = 36 hours
- 16 times AWS Academy self paced sessions: 16 x 1h = 16 hours

Home work:
- Working with assignments: approximately 80 hours

Total: approximately 135 hours

Content scheduling

The course content is divided into four learning objectives(CLOs):

CLO1 Analyze classic data centers and cloud data center solutions.

Introduction to Cloud Computing
1.1 Understand the limitations of traditional computing and evolution of cloud computing
1.2 Understand the concepts of Cluster, Grid and Cloud Computing, its benefits and challenges

Cloud Computing Models and Services
1.3 Explore the standard cloud model, cloud deployment and service delivery models
1.4 Understand service abstraction

Resource Virtualization and Pooling
1.5 Implement physical computing resources virtualization
1.6 Implement machine, server level and operating system virtualization
1.7 Understand resource pooling, sharing and resource provisioning

CLO2 Design a cloud data center based on specific technical requirements.

Resource Virtualization and Pooling
2.1 Implement physical computing resources virtualization
2.2 Implement machine, server level and operating system virtualization

Scaling and Capacity Planning
2.3 Understand the foundation of cloud scaling
2.4 Explore scaling strategies and implement scalable applications
2.5 Explore approaches for capacity planning

Load Balancing
2.6 Explore the goals and categories of load balancing. Explore parameters for consideration.

File System and Storage
2.7 Understand the need for high performance processing and Big Data
2.8 Explore storage deployment models and differentiate various storage types

CLO3 Discuss the need for security, reliability and legal compliance of a cloud data center.
Database Technologies
3.1 Explore database models
3.2 Implement relational and non-relational database as a service

Cloud Computing Security
3.3 Understand the threats to cloud security
3.5 Explore and develop a cloud security model
3.6 Understand Trusted Cloud Computing

Privacy and Compliance
3.7 Explore key privacy concerns in the cloud
3.8 Differentiate security vs. privacy
3.9 Develop a privacy policy

CLO4 Design strategies for the implementation of effective cloud solutions to support business requirements.

Content Delivery Model
4.1 Understand and explore content delivery network models in the cloud

Portability and Interoperability
4.2 Explore portability and interoperability scenarios
4.3 Understand machine imaging
4.4 Differentiate virtual machine and virtual appliance

Cloud Management
4.5 Understand cloud service life cycle
4.6 Understand asset management in the cloud
4.7 Explore cloud service management
4.8 Develop disaster recovery strategies

SELF PACED / FLIP CLASSROOM
In addition to the above theoretical content the students will learn and practice the cloud concepts in AWS academy. The AWS academy online course covers the following modules.

Module 1 - Global Infrastructure
Module 2 - Structures of the Cloud
Module 3 - AWS Console
Module 4 - Virtual Servers
Module 5 - Content Delivery
Module 6 - Virtual Storage
Module 7 - Security 1
Module 8 - Security 2
Module 9 - Monitoring the Cloud
Module 10: Databases
Module 11 - Load Balancers and Caching
Module 12 - Elastic Beanstalk and Cloud Formation
Module 13 - Emerging Technologies in the Cloud
Module 14 - Billing and Support
Module 15 - Other Cloud Features
Module 16 - Optimizing the Cloud with the AWS CDK

Further information

Course material and assignments in Its Learning and AWS academy.

Evaluation scale

H-5

Assessment methods and criteria

Personal assignments: 50 points
AWS Academy Course labs: 30 points
Project: 20 points

The assignments must be returned by the deadline to get the points. The assignments returned after the deadline will give you only half of the points.
Demonstrations of exercises during the contact session is mandatory without demonstration you will lose 50% of your marks.

The grading scale (points -> grade):

50 points -> 1
60 points -> 2
70 points -> 3
80 points -> 4
90 points -> 5

Assessment criteria, fail (0)

Fail < 50 points

Assessment criteria, satisfactory (1-2)

50 points -> 1
60 points -> 2

Assessment criteria, good (3-4)

70 points -> 3
80 points -> 4

Assessment criteria, excellent (5)

90 points -> 5

Objective

After completing the course, the student can:
- Describe what Cloud Services are, how they affect business and which new opportunities it may enable.
- Describe use cases and benefits of cloud services,
- Describe SAAS, PAAS, IAAS.
- Develop a solution that utilizes cloud services.

Content

Introduction to cloud services
Software as a service (SAAS)
Platform as a service (PAAS)
Infrastructure as a service (IAAS)
Virtual machines and containers
Security of cloud services
Project work

Materials

Task-specific material to be announced separately in Its Learning and in AWS academy.

Teaching methods

- Weekly face-to-face meetings with lecture teaching and small group work
- Learning by doing and experimenting (exercise tasks, project work, information search)
- Small group work and peer learning
- Self-study material
- Teacher guidance and examples

Exam schedules

No exam, and retake not possible after evaluation grade is published.

International connections

FLIP classrooms and learning by doing

Completion alternatives

Not possible

Student workload

Contact hours
- Course introduction: 3 hours
- 12 times 2h theory: 12 x 2h = 24 hours
- 12 times 1h AWS Support: 12 x 1h = 12 hours
- 16 times AWS Academy self paced sessions: 16 x 1h = 16 hours

Home work:
- Working with assignments: approximately 80 hours

Total: approximately 135 hours

Content scheduling

The course content is divided into four learning objectives(CLOs):

CLO1 Analyze classic data centers and cloud data center solutions.

Introduction to Cloud Computing
1.1 Understand the limitations of traditional computing and evolution of cloud computing
1.2 Understand the concepts of Cluster, Grid and Cloud Computing, its benefits and challenges

Cloud Computing Models and Services
1.3 Explore the standard cloud model, cloud deployment and service delivery models
1.4 Understand service abstraction

Resource Virtualization and Pooling
1.5 Implement physical computing resources virtualization
1.6 Implement machine, server level and operating system virtualization
1.7 Understand resource pooling, sharing and resource provisioning

CLO2 Design a cloud data center based on specific technical requirements.

Resource Virtualization and Pooling
2.1 Implement physical computing resources virtualization
2.2 Implement machine, server level and operating system virtualization

Scaling and Capacity Planning
2.3 Understand the foundation of cloud scaling
2.4 Explore scaling strategies and implement scalable applications
2.5 Explore approaches for capacity planning

Load Balancing
2.6 Explore the goals and categories of load balancing. Explore parameters for consideration.

File System and Storage
2.7 Understand the need for high performance processing and Big Data
2.8 Explore storage deployment models and differentiate various storage types

CLO3 Discuss the need for security, reliability and legal compliance of a cloud data center.
Database Technologies
3.1 Explore database models
3.2 Implement relational and non-relational database as a service

Cloud Computing Security
3.3 Understand the threats to cloud security
3.5 Explore and develop a cloud security model
3.6 Understand Trusted Cloud Computing

Privacy and Compliance
3.7 Explore key privacy concerns in the cloud
3.8 Differentiate security vs. privacy
3.9 Develop a privacy policy

CLO4 Design strategies for the implementation of effective cloud solutions to support business requirements.

Content Delivery Model
4.1 Understand and explore content delivery network models in the cloud

Portability and Interoperability
4.2 Explore portability and interoperability scenarios
4.3 Understand machine imaging
4.4 Differentiate virtual machine and virtual appliance

Cloud Management
4.5 Understand cloud service life cycle
4.6 Understand asset management in the cloud
4.7 Explore cloud service management
4.8 Develop disaster recovery strategies

SELF PACED / FLIP CLASSROOM
In addition to the above theoretical content the students will learn and practice the cloud concepts in AWS academy. The AWS academy online course covers the following modules.

Introduction
Module 1 - Cloud Concepts Overview
Module 2 - Cloud Economics and Billing
Module 3 - AWS Global Infrastructure Overview
Module 4 - AWS Cloud Security
Module 5 - Networking and Content Delivery
Module 6 - Compute
Module 7 - Storage
Module 8 - Databases
Module 9 - Cloud Architecture
Module 10 - Auto Scaling and Monitoring

Further information

Course material and assignments in Its Learning and AWS academy.

Evaluation scale

H-5

Assessment methods and criteria

Personal assignments: 50 points
AWS Academy Course labs: 30 points
Project: 20 points

The assignments must be returned by the deadline to get the points. The assignments returned after the deadline will give you only half of the points.
Demonstrations of exercises during the contact session is mandatory without demonstration you will lose 50% of your marks.

The grading scale (points -> grade):

50 points -> 1
60 points -> 2
70 points -> 3
80 points -> 4
90 points -> 5

Assessment criteria, fail (0)

Fail < 50 points

Assessment criteria, satisfactory (1-2)

50 points -> 1
60 points -> 2

Assessment criteria, good (3-4)

70 points -> 3
80 points -> 4

Assessment criteria, excellent (5)

90 points -> 5

Objective

After completing the course the student:
is familiar with the basic concepts and principles of cryptology
understands some mathematical backgrounds of cryptography
knows how symmetric and asymmetric ciphers function
can explain the workings of some cryptographic applications

Content

• basic concepts and principles of cryptology
• mathematical backgrounds of cryptography
• symmetric and asymmetric ciphers
• some up to date cryptographic applications

Location and time

September – December 2018.

Materials

Lecture notes, exercises, various internet sources, links & descriptions are provided in Itslearning.

A Graduate Course in Applied Cryptography by D. Boneh and V. Shoup (Version 0.6, January 2023). Available online: https://toc.cryptobook.us/book.pdf
Understanding Cryptography by C. Paar and J. Pelz (Springer, 2010). Available in the library. Some chapters are available for free online.

Teaching methods

Classroom activities, group work and independent work; project work, task-based (homework).

Exam schedules

Final exam 10.12.2024

International connections

The contents of the course give understanding of the basic cryptographic tools and devices which are essential in the operating environment of an ICT engineer, such as all electronic and wireless communications, e-commerce applications etc.

Students will team up for a project work on some current and relevant aspect of cryptology. The teams will present their work to the whole group, which gives everyone a broader understanding on the topic.

Task-based assessment supports learning and is continuous throughout the course. Studying in an international group develops students’ ability to intercultural communication and multicultural collaboration.

Completion alternatives

You get points from the homework, the project work, and the final exam.
Homework points are granted only when it's done properly and submitted in time in the respective Itslearning HW box.
Project work points are granted separately from the report and the presentation.
There is no way to compensate for missing a homework deadline or the project work submission deadline.

To pass the course, you need to gain at least 40 % of the total points
and either

a) at least 40 % of the final exam points
or

b) 75 % classroom attendance and an approved project participation.

Student workload

Classroom activities participation + preparation 40 h
Homework 40 h
Project work 30 h
Final exam + preparation 15 h

Content scheduling

• basic concepts and principles of cryptology
• mathematical backgrounds of cryptography
• symmetric and asymmetric ciphers
• some up to date cryptographic applications

September - December 2024

Further information

For timetables, see lukkari.turkuamk.fi.
Other practical information & materials available in Itslearning.

Evaluation scale

H-5

Assessment methods and criteria

Weekly classroom activities + homework 60 %.
Project report and presentation 20 %.
Final exam 20 %. (A written exam on specified material.)

You need to achieve 40 % of total points to pass the course.
Additionally, you need to
1. attain 75 % active classroom attendance + approved project participation
OR
2. attain at least 40 % of the final exam points.

Assessment criteria, fail (0)

Student has not demonstrated achieving the learning objectives of the course. They recognize and can use only few of the concepts of the course topics, and show no skills to apply them.
Student has not achieved 40 % of total points OR has failed to meet one of the passing conditions of the course.

Assessment criteria, satisfactory (1-2)

Student has demonstrated having achieved the learning objectives of the course on satisfactory level. They recognize and can to some extent use most of the concepts of the course topics.

Assessment criteria, good (3-4)

Student has demonstrated having achieved the learning objectives of the course well.
They recognize and can use most of the concepts of the course topics, and are able to apply them on various study and work contexts.

Assessment criteria, excellent (5)

Student has demonstrated having achieved the learning objectives of the course on excellent level. They master the concepts of the course topics, and are able to fluently apply them on study and work contexts.

Qualifications

Basics of Mathematical Analysis, Number Theory and Algorithmics

Materials

Learning material consists of material produced by the Lecturer as well as extra material obtainable from TUAS resources (ebooks).

Teaching methods

Learning is achieved through contact lectures, written home assignments and laboratory assignments.

Exam schedules

The course exam will take place in Itslearning on week 48/2024.

Re-take opportunities will be provided on week 49 and 50 (2 sessions).

Content scheduling

The course consists of contact lectures and contact laboratory sessions. There will be 9 lectures, which will cover theory and technologies related Cybersecurity in Industrial Networks. In 5 laboratory sessions, students will get to know relevant aspects and protocols used in industrial networks through laboratory assignments.

The course will begin on week 22/2024 and end by week 50/2024.

Evaluation scale

H-5

Assessment methods and criteria

Each home assignment and laboratory assignment will be evaluated separately.

There will be 3 written home assignments and 6 laboratory assignments. Home assignments will each be valued 10 points and laboratory assignments will each be valued on average at 5 points. The maximum points for the course exam will be 40 points. The total points for the course will be 100 points and the grading will be as follows:

Home assignments 30 p
Laboratory assignments 30 p
+ optional bonus labs 20 p
Course examination 40 p

49 and less = Failed
50-59 pts = 1
60-69 pts = 2
70-79 pts = 3
80-89 pts = 4
90 and more = 5

Course lecture and lab session attendance will be monitored. Minimum of 50% attendance in the contact sessions is required to pass the course. Possible exceptions must be discussed with the lecturer by each student separately.

Objective

After completing the course the student:
- Can define the main concepts related to data analytics and machine learning
- Understands the value and the drivers for data analytics and machine learning
- Can describe the processes of data analytics and machine learning
- Can use some tools for data analytics and machine learning

Content

Introduction to data analytics and machine learning
Data analytics process and methods
Machine learning process and methods
Practical work

Materials

Course book:

Aurélien Géron.
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow
2nd Edition.
Publisher : O'Reilly Media; 2nd edition
(October 15, 2019)

We study chapters 1, 2, 3, 4, 6, 9, and 10 of the book. They have about 300 pages, but some are skipped over.

The course book can be read in electronic form from our institution's eBook Central database.

The course also has reading material, which will be announced during the course.

Teaching methods

- Participating in lectures (theory and practice)
- Learning through hands-on programming (classwork assignments)
- Completing homework assignments
- Interacting with the teacher and classmates
- Enhancing knowledge through teamwork projects
- Following the flipped-classroom model (pre-session self-study of theoretical concepts followed by in-class practical application)

Exam schedules

No exam!

International connections

- The course includes approximately 14 theory and practice sessions, where students engage with practical tasks.
- Homework exercises will be assigned, with some parts demonstrated during contact sessions.
- A teamwork project will be introduced in the second month, requiring students to apply their teamwork skills and the knowledge gained from the course to implement their final project.
- A flipped-classroom model may be used for some lectures, where students study the theoretical content at home and focus on practical implementation and discussions during class.

Completion alternatives

The practice works and exercises are mainly performed using Python and Jupyter Notebook.

Student workload

+ Student Responsibilities:
1. Class Participation and Assignments:
- Active participation in all classes, including the completion of in-class assignments, which must be submitted during class hours.
2. Homework Assignments:
- Completing 8-10 individual homework assignments, partially demonstrated during contact sessions. The exact number of the assignments will be announced at the first lecture)
3. Final Project:
- A group project (2-3 students) to be completed over Weeks 46 & 47, culminating in a presentation in Week 48.

+ Student workload:
Contact hours (approximately):
- One introductionary session: 2h
- 13 times 3h theory and practice: 13 x 3h = 39 hours
- Final projects and presentations: 24 hours
- Home work: approximately 75 hours

Total: approximately: 140 hours

Content scheduling

+ The course includes approximately 14 guided working and theory sessions, 9 personal homework assignments, 8-9 classwork assignment and a teamwork project

+ Final project is done in groups of 2-3 people outside of guidance sessions. The group sets aside 15 minutes to present the group work during the last session.

+ Content scheduling
- Week 03: Course Introduction (2h)
- Week 04: Landscape of machine learning (3h)
- Week 05: Data exploration (3h)
- Week 06: Data preparation (3h)
- Week 07: Model training, selection, and evaluation (3h)
- Week 08: Winter break - Visualization (self-study)
- Week 09: Demonstrations of Exercises 1 – 4 (3h)
- Week 10: Classification (3h)
- Week 11: Training models (3h)
- Week 12: Decision trees (3h)
- Week 13: Unsupervised learning (3h)
- Week 14: Guidance to team work (3h)
- Week 15: Introduction to Neural networks (3h)
- Week 16: Demonstrations of Exercises 5 – 9 (3h)
- Week 17: Team work presentations (3h)

Further information

+ Qualifications:
- Python programming skills and skills in utilizing Pandas for data manipulation and Numpy for numerical operations and array handling
- Basic knowledge of probability, statistics and linear algebra

+ Communication Channel:
Itslearning and email

Evaluation scale

H-5

Assessment methods and criteria

1) The course is graded on a scale of 0-5

2) Students can achieve maximum 200 points from this course that contains:
- Participation and classwork assignments: participating on each lecture and submitting the related classwork assignment during the class hours 1+2 = 3p => 9 X 4 = 36 points.
- Homework assignments: each homework assignment has 10-15 points. There are 9 homework assignments =>minimum 90 points and maximum 135 points.
- Teamwork assignment: 29 points

Assessment criteria, fail (0)

The student did NOT get at least 50% of the points in teamwork assignment OR did not get at least 50% of the points in the homework assignments OR did not get at least 50% of the points in participation and classwork submission.

Assessment criteria, satisfactory (1-2)

The student got 50-65% of the points for the homework assignments AND got 50-65% of the points for the participation and classwork assignments submission AND got 50-65% of the points for the teamwork assignment.

Assessment criteria, good (3-4)

The student got 66-85% of the points for the homework assignments AND got 66-85% of the points for the participation and classwork assignments submission AND got 66-85% of the points for the teamwork assignment.

Assessment criteria, excellent (5)

The student got at least 86% of the points for the homework assignments AND got at least 86% of the points for the participation and classwork assignments submission AND got at least 86% of the points for the teamwork assignment.

Objective

After completing the course the student can:
- explain the most common data structures
- apply the most common data structures and algorithms connected to the use of these structures
- evaluate the efficiency of algorithms.

Content

- lists, stacks, queues, trees, graphs and hash tables
- analysing and evaluating algorithms   
- designing algorithms       
- sorting methods  
- search algorithms

Materials

Material available via the learning environment (ITS).

Teaching methods

Weekly contact 3 hours sessions for theory and practical exercises.
Additionally, if needed weekly 1h sessions for questions and support in exercises.

Exam schedules

No exam, and retake not possible after evaluation grade is published.

International connections

The course has 12 three-hour contact sessions where teacher present theory and examples and students work with practical tasks.
Additionally, students are able to receive extra guidance for exercises.

Electronic materials are used in the course. In addition, guidance is also organized online in order to reduce the carbon footprint caused by movement.

Completion alternatives

Not possible

Student workload

Contact hours
- Course introduction: 3 hours
- 13 times 2h theory: 13 x 2h = 26 hours
- 13 times 1h demo 13 x 1h = 13 hours - Group 1
- 13 times 1h demo 13 x 1h = 13 hours - - Group 2
- FLIP Classroom 10 X 1h = 10h
Home work:
- Working with assignments: approximately 80 hours


Total: approximately 130 hours

Content scheduling

Week 36: Course introduction

Session from Weeks 36 - 48
- Algorithms and algorithmic thinking
- Data structures
- Search algorithms
- Sorting algorithms

Contact hours according to lukkari.turkuamk.fi.

Further information

ITS and Teams.

Evaluation scale

H-5

Assessment methods and criteria

The course is graded on a scale of 0-5.

You can achieve 80 points from practical exercises in class room and home work exercises.
Around half of the exercises are done during the contact hours.

Demonstrations of exercises during the contact session is mandatory without demonstration you will lose 50% of your marks.

Additionally, there is a group project of 20 points, passing group project is mandatory to pass the course.

Lastly, to pass the course the student need to get at least 40 marks in the exercises and at least 10 marks in the project.

Assessment criteria, fail (0)

Less than 50% points in the exercises OR Student does not passed the group project.

Assessment criteria, satisfactory (1-2)

50 points -> 1
60 points -> 2

Assessment criteria, good (3-4)

70 points -> 3
80 points -> 4

Assessment criteria, excellent (5)

90 points -> 5

Qualifications

Introduction to Programming, or equivalent programming skills

Objective

After completing the course the student can:
- explain the most common data structures
- apply the most common data structures and algorithms connected to the use of these structures
- evaluate the efficiency of algorithms.

Content

- lists, stacks, queues, trees, graphs and hash tables
- analysing and evaluating algorithms
- designing algorithms
- sorting methods
- search algorithms

Materials

Material available via the learning environment (ITS).

Teaching methods

Weekly contact 3 hours sessions for theory and practical exercises.
Additionally, if needed weekly 1h sessions for questions and support in exercises.

Exam schedules

No exam, and retake not possible after evaluation grade is published.

International connections

The course has 12 three-hour contact sessions where teacher present theory and examples and students work with practical tasks.
Additionally, students are able to receive extra guidance for exercises.

Electronic materials are used in the course. In addition, guidance is also organized online in order to reduce the carbon footprint caused by movement.

Completion alternatives

Not possible

Student workload

Contact hours
- Course introduction: 3 hours
- 13 times 2h theory: 13 x 2h = 26 hours
- 13 times 1h demo 13 x 1h = 13 hours - Group 1
- 13 times 1h demo 13 x 1h = 13 hours - - Group 2
- FLIP Classroom 10 X 1h = 10h
Home work:
- Working with assignments: approximately 80 hours


Total: approximately 130 hours

Content scheduling

Week 36: Course introduction

Session from Weeks 36 - 48
- Algorithms and algorithmic thinking
- Data structures
- Search algorithms
- Sorting algorithms

Contact hours according to lukkari.turkuamk.fi.

Further information

ITS and Teams.

Evaluation scale

H-5

Assessment methods and criteria

The course is graded on a scale of 0-5.

You can achieve 80 points from practical exercises in class room and home work exercises.
Around half of the exercises are done during the contact hours.

Demonstrations of exercises during the contact session is mandatory without demonstration you will lose 50% of your marks.


Additionally, there is a group project of 20 points, passing group project is mandatory to pass the course.

Lastly, to pass the course the student need to get at least 40 marks in the exercises and at least 10 marks in the project.

Assessment criteria, fail (0)

Less than 50% points in the exercises OR Student does not passed the group project.

Assessment criteria, satisfactory (1-2)

50 points -> 1
60 points -> 2

Assessment criteria, good (3-4)

70 points -> 3
80 points -> 4

Assessment criteria, excellent (5)

90 points -> 5

Qualifications

Introduction to Programming, or equivalent programming skills

Objective

After completing the course the student can:
- explain the most common data structures
- apply the most common data structures and algorithms connected to the use of these structures
- evaluate the efficiency of algorithms.

Content

- lists, stacks, queues, trees, graphs and hash tables
- analysing and evaluating algorithms   
- designing algorithms       
- sorting methods  
- search algorithms

Materials

Lecture and practice session material in ItsLearning, e.g. PowerPoint presentations, Jupyter notebook / Python files, etc.
All material is provided in English

Teaching methods

Attending to lectures: teacher will provide both theoretical background and practical examples on a dedicated topic
Attending practice sessions: the theory is put into action in practice - we will see solutions to previous exercises + practice new topics
Individual work: Completing the assignments individually after face-to-face sessions

Exam schedules

No exam, retake not possible after the publication of the final assessment/course grade

International connections

The course has 14 two-hour contact sessions where teacher present theory and examples, and 12 two-hour practice sessions where students work with practical tasks.

Electronic materials are used in the course.

Completion alternatives

Ask teacher, if there is an ongoing suitable online course (FiTech / Coursera or equivalent).
CampusOnline courses ARE NOT accepted!

Student workload

Lectures 2h / week x 14 = 28h
Practice sessions 2h x 12 = 24h
Individual work outside school: reading, studying, preparing the weekly programming practice tasks: 80h

Total: approx. 80h

Content scheduling

Understanding data structures and algorithmic efficiency / complexity are essential in many ways. During this course, the student will gain both theoretical and practical understanding on these topics. Students will learn to use pseudocode / flowcharts to describe algorithms and analyze their complexity (time and space, both experimental and theoretical). We will gain a comprehensive insight to elementary data structures and their algorithms.

Practical understanding is gained through coding exercises. We will use Python as our main coding language.

January– April 2025

January: Algorithmic Thinking and Analysis
• pseudocode, flowcharts
• efficiency and algorithmic complexity

February: Basic Data Structures
• Arrays, Linked List, Stack, Queue

March: Advanced Data Structures
• Hash table, Trees, Graphs

April: Sorting Algorithms, Search Algorithms
• Bubble, Selection, Insertion, Merge and Quick Sort

Further information

ItsLearning
Email

Evaluation scale

H-5

Assessment methods and criteria

The grade will be based on the following criteria:
- practical work (at the end of the course)
- homework activity (continuous, weekly assignments)
- attendance to lectures and practice sessions

You can achieve 80 points from practical exercises in class room and home work exercises.
Around half of the exercises are done during the contact hours.

Demonstrations of exercises during the contact session is mandatory without demonstration you will lose 50% of your marks.

Additionally, there is a group project of 20 points, passing group project is mandatory to pass the course.

Lastly, to pass the course the student need to get at least 40 marks in the exercises and at least 10 marks in the project.

Assessment criteria, fail (0)

Student fails to meet most of the general objectives of the course in a satisfactory level.

Assessment criteria, satisfactory (1-2)

• has an elementary understanding on the performance of algorithms and in simple cases is able to apply some methods of analysis covered during the course.
• is familiar with some major algorithms and data structures covered in the course.
• has a basic understanding on how to apply the algorithmic design parameters covered in the course.
• has an elementary understanding on data representation.
• demonstrates some understanding on how to decompose programming problems in a purposeful way.
• can use most elementary data structures appropriately

Assessment criteria, good (3-4)

• can analyze the performance of simple algorithms and is able to apply some of the methods of analysis covered during the course.
• is familiar with most of the major algorithms and data structures covered in the course.
• has an understanding of the algorithmic design parameters covered in the course.
• has a good understanding on data representation.
• demonstrates ability to decompose programming problems in a somewhat purposeful way.
• can choose and use elementary data structures appropriately in most cases.

Assessment criteria, excellent (5)

• can analyze the performance of algorithms and is able to apply all the methods of analysis covered during the course.
• is familiar with all the major algorithms and data structures covered in the course.
• is able to apply the algorithmic design parameters covered in the course.
• has a deep understanding on data representation.
• demonstrates ability to decompose programming problems in a purposeful way.
• can choose and use elementary data structures appropriately.

Qualifications

Introduction to Programming, or equivalent programming skills

Objective

After completing the course the student can:
- understand different types of databases and evaluate their feasibility for different purposes.
- plan and implement a database based on requirements and search and modify data in the database
- use at least one well-known database management system
- describe database management tasks

Content

- Different types of databases
- Definition, planning and implementation of databases
- SQL basics
- Database administration with DBMS
- Management principles for databases

Materials

Lecture slides and examples by the teacher
Lot of internet material available
Supporting books about relational databases and SQL are available in Internet.
MongoDB has good tutorials and documentation as well.

Teaching methods

The course consists of
1) lecture and home exercises (small queries and design tasks)
2) personal practical work (creating your own database) and
3) exam (testing your acquired skills).

Lecture exercises are divided into weekly topics. Each week introduces a new topic that builds on top of previous weeks. Each lecture begins with an introduction to the topic of the week, which includes practical examples and learning material. Exercises are done individually or in small groups with the help of the teacher .

NOTE! Lecture exercises can be returned only by participating in the lecture session!

Exam schedules

The exam is performed in ViLLE system www.ville.utu.fi which supports SQLite.
1st exam is organized in the class room (during the regular meeting time: the last lecture time) where Internet use is allowed for information retrieval.
Re-exams, i.e. 2nd and 3rd exams, are e-exams in the e-exam room premises (EduCity, Library) where Internet use is not allowed. E-exams are open 6 months after the course has ended.

International connections

- Learning by doing and trial&error with lecture exercises,
- Introductory lectures and examples provided by the teacher.
- Collaborating with other students in the lectures.

Completion alternatives

Participation in the lecture is not compulsory, but exercises can be returned only during the lecture.

Online course is available for those whose attendance in lectures is not possible. This self-study option has slightly different emphasis of topics and grading. These will be introduced in the beginning of the course in the first lecture. Students can choose their preferred method after the first lecture.

Student workload

Participating weekly in lectures (exercises): a' 3 hours * 13 = 40h
Home exercises 10h
Individual practical work 60h
Exam 3 hours + preparing 20h

Student workload is about 5-8 h / week if you are new to relational databases.

Content scheduling

In this course, students learn to use and design relational databases as well as understand differences to NoSQL/document databases. First, students familiarize with database thinking and the principles of data management from a quality perspective. Key topics include data modeling using ER diagrams, relational schema representations and normalization technique for validating the quality of the database design. Second, students apply structured query language (SQL) to create a database (SQL DDL), and to manipulate and search data in the database (SQL DML). Last, students learn differences between SQL and NoSQL databases through desinging and using MongoDB document database. The course consists of lectures, exercises, a practical work and final exam.

Topics (and hours used in teaching sessions) in the order of appearance:
- Relational DBMS and DB use 6h
- Relational database design 9h
- Basics of SQL 18h
- Introduction to document database MongoDB 6h

Further information

All returns and communications take place through the It's Learning platform (except for the online course).

There are no pre-requisites for course performance in this course, and this course does not require previously acquired skills. It is necessary to have your own computer and know how to use it.
We use the relational database and its management environment for practical training (MySQL, MariaDB, SQLite or similar used in UwAmp, XAMPP or WAMP or similar) and must be installed on the student's personal computer. The necessary applications are installed in a lecture together.
In addition to relational databases, students learn about MongoDB cloud services, Mongo Shell, and practice designing and using a document-based database.

Evaluation scale

H-5

Assessment methods and criteria

The course is graded from 0-5. The grade is based on collected points during the course.
Each returned exercise is 1 point unless mentioned otherwise. The exam is compulsory part and must be passed with 40% of total points of the exam, in order to pass the course.

Division of points:
Lecture and home exercises 70 p points in total
Practical work 60 points
Exam 70 p points
Total 200 points

Course grading:
Points Grade
0-99 NOT PASSED
100-119 1
120-139 2
140-159 3
160-179 4
180-200 5

Assessment criteria, fail (0)

Less than 50% of total points collected or the exam is failed (less than 40% of total points of the exam). Check the points-to-grade table

Assessment criteria, satisfactory (1-2)

- Is able to implement relational database management software (DBMS) and know the tasks related to database maintenance
- Is able to design a relational database using conceptual model technique (ER or similar notation)
- Can implement a relational database with SQL statements
- Can retrieve, add and edit data in a relational database with simple SQL statements
- Knows different types of databases and their uses

Less than 70% of total points collected.

Assessment criteria, good (3-4)

In addition
- Can interpret the concept model and implement a relational database based on it
- Understands the meaning and use of keys and reference integrity in relational databases
- Is able to use SQL statements for data retrieval in various ways, such as combining data from different tables
- Understands the principle and purpose of normalization
- Can introduce non-relational databases and evaluate their suitability for different purposes (MongoDB)


70-90% of total points collected.

Assessment criteria, excellent (5)

In addition
- Is able to independently develop a high-quality concept model based on the user requirements
- Can use normalization to improve the quality of a relational database
- Can use SQL statements for information retrieval in various ways, such as sub-groupings and sub-queries
- Can do basic queries and design a simple NoSQL database (MongoDB)

More than 90% of total points collected.

Qualifications

Computer Skills

Objective

After completing the course the student can:
- understand different types of databases and evaluate their feasibility for different purposes.
- plan and implement a database based on requirements and search and modify data in the database
- use at least one well-known database management system
- can describe database management tasks

Content

- Different types of databases
- Definition, planning and implementation of databases
- SQL basics
- Database administration in DBMS

Materials

Lecture slides and examples by the teacher
Lot of internet material available
Supporting books about relational databases and SQL are available in Internet.
MongoDB has good tutorials and documentation as well.

Teaching methods

The course consists of
1) lecture and home exercises (small queries and design tasks)
2) personal practical work (creating your own database) and
3) exam (testing your acquired skills).

Lecture exercises are divided into weekly topics. Each week introduces a new topic that builds on top of previous weeks. Each lecture begins with an introduction to the topic of the week, which includes practical examples and learning material. Exercises are done individually or in small groups with the help of the teacher .

NOTE! Lecture exercises can be returned only by participating in the lecture session!

Exam schedules

The exam is performed in ViLLE system www.ville.utu.fi which supports SQLite.
1st exam is organized in the class room (during the regular meeting time: the last lecture time) where Internet use is allowed for information retrieval.
Re-exams, i.e. 2nd and 3rd exams, are e-exams in the e-exam room premises (EduCity, Library) where Internet use is not allowed. E-exams are open 6 months after the course has ended.

International connections

- Learning by doing and trial&error with lecture exercises,
- Introductory lectures and examples provided by the teacher.
- Collaborating with other students in the lectures.

Completion alternatives

Participation in the lecture is not compulsory, but exercises can be returned only during the lecture.

Online course is available for those whose attendance in lectures is not possible. This self-study option has slightly different emphasis of topics and grading. These will be introduced in the beginning of the course in the first lecture. Students can choose their preferred method after the first lecture.

Student workload

Participating weekly in lectures (exercises): a' 3 hours * 13 = 40h
Home exercises 10h
Individual practical work 60h
Exam 3 hours + preparing 20h

Student workload is about 5-8 h / week if you are new to relational databases.

Content scheduling

In this course, students learn to use and design relational databases as well as understand differences to NoSQL/document databases. First, students familiarize with database thinking and the principles of data management from a quality perspective. Key topics include data modeling using ER diagrams, relational schema representations and normalization technique for validating the quality of the database design. Second, students apply structured query language (SQL) to create a database (SQL DDL), and to manipulate and search data in the database (SQL DML). Last, students learn differences between SQL and NoSQL databases through desinging and using MongoDB document database. The course consists of lectures, exercises, a practical work and final exam.

Topics (and hours used in teaching sessions) in the order of appearance:
- Relational DBMS and DB use 6h
- Relational database design 9h
- Basics of SQL 18h
- Introduction to document database MongoDB 6h

Further information

All returns and communications take place through the It's Learning platform (except for the online course).

There are no pre-requisites for course performance in this course, and this course does not require previously acquired skills. It is necessary to have your own computer and know how to use it.
We use the relational database and its management environment for practical training (MySQL, MariaDB, SQLite or similar used in UwAmp, XAMPP or WAMP or similar) and must be installed on the student's personal computer. The necessary applications are installed in a lecture together.
In addition to relational databases, students learn about MongoDB cloud services, Mongo Shell, and practice designing and using a document-based database.

Evaluation scale

H-5

Assessment methods and criteria

The course is graded from 0-5. The grade is based on collected points during the course.
Each returned exercise is 1 point unless mentioned otherwise. The exam is compulsory part and must be passed with 40% of total points of the exam, in order to pass the course.

Division of points:
Lecture and home exercises 70 p points in total
Practical work 60 points
Exam 70 p points
Total 200 points

Course grading:
Points Grade
0-99 NOT PASSED
100-119 1
120-139 2
140-159 3
160-179 4
180-200 5

Assessment criteria, fail (0)

Less than 50% of total points collected or the exam is failed (less than 40% of total points of the exam). Check the points-to-grade table

Assessment criteria, satisfactory (1-2)

- Is able to implement relational database management software (DBMS) and know the tasks related to database maintenance
- Is able to design a relational database using conceptual model technique (ER or similar notation)
- Can implement a relational database with SQL statements
- Can retrieve, add and edit data in a relational database with simple SQL statements
- Knows different types of databases and their uses

Less than 70% of total points collected.

Assessment criteria, good (3-4)

In addition
- Can interpret the concept model and implement a relational database based on it
- Understands the meaning and use of keys and reference integrity in relational databases
- Is able to use SQL statements for data retrieval in various ways, such as combining data from different tables
- Understands the principle and purpose of normalization
- Can introduce non-relational databases and evaluate their suitability for different purposes (MongoDB)


70-90% of total points collected.

Assessment criteria, excellent (5)

In addition
- Is able to independently develop a high-quality concept model based on the user requirements
- Can use normalization to improve the quality of a relational database
- Can use SQL statements for information retrieval in various ways, such as sub-groupings and sub-queries
- Can do basic queries and design a simple NoSQL database (MongoDB)

More than 90% of total points collected.

Objective

After completing the course the student can:
- understand different types of databases and evaluate their feasibility for different purposes.
- plan and implement a database based on requirements and search and modify data in the database
- use at least one well-known database management system
- can describe database management tasks

Content

- Different types of databases
- Definition, planning and implementation of databases
- SQL basics
- Database administration in DBMS

Materials

Lecture slides and examples by the teacher
Lot of internet material available
Supporting books about relational databases and SQL are available in Internet.
MongoDB has good tutorials and documentation as well.

Teaching methods

The course consists of
1) lecture and home exercises (small queries and design tasks)
2) personal practical work (creating your own database) and
3) exam (testing your acquired skills).

Lecture exercises are divided into weekly topics. Each week introduces a new topic that builds on top of previous weeks. Each lecture begins with an introduction to the topic of the week, which includes practical examples and learning material. Exercises are done individually or in small groups with the help of the teacher .

NOTE! Lecture exercises can be returned only by participating in the lecture session!

Exam schedules

Not decided

International connections

- Learning by doing and trial&error with lecture exercises,
- Introductory lectures and examples provided by the teacher.
- Collaborating with other students in the lectures.

Completion alternatives

Participation in the lecture is not compulsory, but exercises can be returned only during the lecture.

Online course is available for those who can't participate on lectures. This self-study option has slightly different emphasis of topics and grading. These will be introduced in the beginning of the course in the first lecture. Students can choose their preferred method after the first lecture.

Student workload

Introduction lecture 2h
Participating weekly in lectures (exercises): a' 3 hours * 13 = 39h
Home exercises 10h
Individual practical work 60h
Exam + preparing 20h

Student workload is about 5-8 h / week if you are new to relational databases.

Content scheduling

In this course, students learn to use and design relational databases as well as understand differences to NoSQL/document databases. First, students familiarize with database thinking and the principles of data management from a quality perspective. Key topics include data modeling using ER diagrams, relational schema representations and normalization technique for validating the quality of the database design. Second, students apply structured query language (SQL) to create a database (SQL DDL), and to manipulate and search data in the database (SQL DML). Last, students learn differences between SQL and NoSQL databases through desinging and using MongoDB document database. The course consists of lectures, exercises, a practical work and final exam.

Topics (and hours used in teaching sessions) in the order of appearance:
- Relational DBMS and DB use 6h
- Relational database design 9h
- Basics of SQL 18h
- Introduction to document database MongoDB 6h

Further information

All returns and communications take place through the It's Learning platform (except for the online course).

There are no pre-requisites for course performance in this course, and this course does not require previously acquired skills. It is necessary to have your own computer and know how to use it.

We use the relational database and its management environment for practical training (MySQL, MariaDB, SQLite or similar used in UwAmp, XAMPP or WAMP or similar) and must be installed on the student's personal computer. The necessary applications are installed in a lecture together.

In addition to relational databases, students learn about MongoDB cloud services, Mongo Shell, and practice designing and using a document-based database.

Evaluation scale

H-5

Assessment methods and criteria

The course is graded from 0-5. The grade is based on collected points during the course.

Each returned exercise is 1 point unless mentioned otherwise. The exam is compulsory part and must be passed with 40% of total points of the exam, in order to pass the course.

Division of points:
Lecture and home exercises 70 points in total
Practical work 60 points
Exam 70 p points
Total 200 points

Course grading:
Points Grade
0-99 NOT PASSED
100-119 1
120-139 2
140-159 3
160-179 4
180-200 5

Assessment criteria, fail (0)

Less than 50% of total points collected or the exam is failed (less than 40% of total points of the exam). Check the points-to-grade table

Assessment criteria, satisfactory (1-2)

- Is able to implement relational database management software (DBMS) and know the tasks related to database maintenance
- Is able to design a relational database using conceptual model technique (ER or similar notation)
- Can implement a relational database with SQL statements
- Can retrieve, add and edit data in a relational database with simple SQL statements
- Knows different types of databases and their uses

Less than 70% of total points collected.

Assessment criteria, good (3-4)

In addition
- Can interpret the concept model and implement a relational database based on it
- Understands the meaning and use of keys and reference integrity in relational databases
- Is able to use SQL statements for data retrieval in various ways, such as combining data from different tables
- Understands the principle and purpose of normalization
- Can introduce non-relational databases and evaluate their suitability for different purposes (MongoDB)

70-90% of total points collected.

Assessment criteria, excellent (5)

In addition
- Is able to independently develop a high-quality concept model based on the user requirements
- Can use normalization to improve the quality of a relational database
- Can use SQL statements for information retrieval in various ways, such as sub-groupings and sub-queries
- Can do basic queries and design a simple NoSQL database (MongoDB)

More than 90% of total points collected.

Objective

After completing the course the student can:
- understand different types of databases and evaluate their feasibility for different purposes.
- plan and implement a database based on requirements and search and modify data in the database
- use at least one well-known database management system
- describe database management tasks

Content

- Different types of databases
- Definition, planning and implementation of databases
- SQL basics
- Database administration with DBMS
- Management principles for databases

Materials

Lecture slides and examples by the teacher
Lot of internet material available
Supporting books about relational databases and SQL are available in Internet.
MongoDB has good tutorials and documentation as well.

Teaching methods

The course consists of
1) lecture and home exercises (small queries and design tasks)
2) personal practical work (creating your own database) and
3) exam (testing your acquired skills).

Lecture exercises are divided into weekly topics. Each week introduces a new topic that builds on top of previous weeks. Each lecture begins with an introduction to the topic of the week, which includes practical examples and learning material. Exercises are done individually or in small groups with the help of the teacher .

NOTE! Lecture exercises can be returned only by participating in the lecture session!

Exam schedules

Not decided.

International connections

- Learning by doing and trial & error with lecture exercises,
- Introductory lectures and examples provided by the teacher.
- Collaborating with other students in the lectures.

Completion alternatives

Participation in the lecture is not compulsory, but exercises can be returned only during the lecture.

Online course is available for those who can't participate on lectures. This self-study option has slightly different emphasis of topics and grading. These will be introduced in the beginning of the course in the first lecture. Students can choose their preferred method after the first lecture.

Student workload

Introduction lecture 2h
Participating weekly in lectures (exercises): a' 3 hours * 13 = 40h
Home exercises 10h
Individual practical work 60h
Exam + preparing 20h

Student workload is about 5-8 h / week if you are new to relational databases.

Content scheduling

In this course, students learn to use and design relational databases as well as understand differences to NoSQL/document databases. First, students familiarize with database thinking and the principles of data management from a quality perspective. Key topics include data modeling using ER diagrams, relational schema representations and normalization technique for validating the quality of the database design. Second, students apply structured query language (SQL) to create a database (SQL DDL), and to manipulate and search data in the database (SQL DML). Last, students learn differences between SQL and NoSQL databases through desinging and using MongoDB document database. The course consists of lectures, exercises, a practical work and final exam.

Topics (and hours used in teaching sessions) in the order of appearance:
- Relational DBMS and DB use 6h
- Relational database design 9h
- Basics of SQL 18h
- Introduction to document database MongoDB 6h

Further information

All returns and communications take place through the It's Learning platform (except for the online course).

There are no pre-requisites for course performance in this course, and this course does not require previously acquired skills. It is necessary to have your own computer and know how to use it.

We use the relational database and its management environment for practical training (MySQL, MariaDB, SQLite or similar used in UwAmp, XAMPP or WAMP or similar) and must be installed on the student's personal computer. The necessary applications are installed in a lecture together.

In addition to relational databases, students learn about MongoDB cloud services, Mongo Shell, and practice designing and using a document-based database.

Evaluation scale

H-5

Assessment methods and criteria

The course is graded from 0-5. The grade is based on collected points during the course.

Each returned exercise is 1 point unless mentioned otherwise. The exam is compulsory part and must be passed with 40% of total points of the exam, in order to pass the course.

Division of points:
Lecture and home exercises 70 p points in total
Practical work 60 points
Exam 70 p points
Total 200 points

Course grading:
Points Grade
0-99 NOT PASSED
100-119 1
120-139 2
140-159 3
160-179 4
180-200 5

Assessment criteria, fail (0)

Less than 50% of total points collected or the exam is failed (less than 40% of total points of the exam). Check the points-to-grade table

Assessment criteria, satisfactory (1-2)

- Is able to implement relational database management software (DBMS) and know the tasks related to database maintenance
- Is able to design a relational database using conceptual model technique (ER or similar notation)
- Can implement a relational database with SQL statements
- Can retrieve, add and edit data in a relational database with simple SQL statements
- Knows different types of databases and their uses

Less than 70% of total points collected.

Assessment criteria, good (3-4)

In addition
- Can interpret the concept model and implement a relational database based on it
- Understands the meaning and use of keys and reference integrity in relational databases
- Is able to use SQL statements for data retrieval in various ways, such as combining data from different tables
- Understands the principle and purpose of normalization
- Can introduce non-relational databases and evaluate their suitability for different purposes (MongoDB)

70-90% of total points collected.

Assessment criteria, excellent (5)

In addition
- Is able to independently develop a high-quality concept model based on the user requirements
- Can use normalization to improve the quality of a relational database
- Can use SQL statements for information retrieval in various ways, such as sub-groupings and sub-queries
- Can do basic queries and design a simple NoSQL database (MongoDB)

More than 90% of total points collected.

Objective

After completing the course the student:
- should be familiar with fundamental electronic circuits.
- is able to design simple analog signal processing functions using operational amplifiers.
- is able to design small signal amplifiers using transistors.

Content

- diodes
- operational amplifiers
- bipolar transistors andMOSFETs

Materials

Lecture materials
Lab instructions in OneNote

Teaching methods

Lectures
Homework
Lab exercises

Exam schedules

To be agreed during the course

International connections

The lectures will introduce the theory required for the lab exercise. Simulations are used to verify the designed circuitry. Implementing and measuring the actual circuits gives deeper understanding and brings hands-on experience on real-world working methods.

Completion alternatives

N/A

Student workload

Lectures 7*2h (14h)
Lab exercises 7 * 3h (21h)
A short exam (1h)

Independent work incl. simulations (99h)

Total: 135h

Content scheduling

The course covers basics of electronics plus some of the typical circuits and components required in embedded systems, when interfacing microcontrollers to the external world.

Further information

Teams-channel of the course

Evaluation scale

H-5

Assessment methods and criteria

Based on:

- Number of completed (and demonstrated) lab exercises
- A short exam

Assessment criteria, fail (0)

Less than 50% lab exercises completed
OR
less than 50% of max points on exam.

Qualifications

Introduction to Electronics and Transmission

Objective

After completing the course the student:
- can design, implement and debug software for embedded Linux platform in IoT context

Content

Embedded IoT application development for Linux platform

Materials

Study material is distributed during the course

Teaching methods

Weekly lab sessions

Exam schedules

TBD

International connections

Instructed lab sessions
Homework
Self-study
A project work
A short exam

Completion alternatives

-

Student workload

Lab sessions and homework 14x8 hours = 112 hours
Self study 165 hours
Project work 8x16=128 hours

Content scheduling

Module implementation has 3 parts
Weeks 1-10:
1) Embedded Linux Application Development: Setting up development tools and cross-compiler, application debugging, Linux application basics, hardware and I/O operations, interrupts
2) Cisco NetAcademy: NDG Linux 1 self-study course
Weeks 11-15:
3) Embedded Linux Project Work: Student teams develop Linux-based IoT system components and systems.

Further information

Itslearning
(Teams)
Gitlab

Evaluation scale

H-5

Assessment methods and criteria

Lab performance and homework 48 points max
Exam 20 points max
Linux systems web course 32 pts

Assessment criteria, fail (0)

Less than 50 (out of 100) points collected from available sources

Assessment criteria, satisfactory (1-2)

1: >50 points
2: >60 points

Assessment criteria, good (3-4)

3: >70 points
4: >80 points

Assessment criteria, excellent (5)

5: >90 points

Qualifications

System software
IoT Essentials

Objective

After completing the course the student can:
- use quantities and units in accordance with the SI system
- solve problems consist of motion
- make graphical presentations and analyze them
- draw free-body diagram
- solve problems involved forces using Newton´s laws
- apply work and conservation of energy to solve problems
- calculate electric and magnetic forces acting on particles and the wave motion of an electro-magnetic fields in engineer’s work
- describe measurement techniques of temperature

Content

- SI system of units
- kinematics, friction
- Newton´s laws with some applications
- work, power and energy
- electric and magnetic fields

Materials

Momentti 1, Insinöörifysiikka, Pentti Inkinen & Jukka Tuohi. Otava.
Momentti 2, Insinöörifysiikka, Pentti Inkinen, Reijo Manninen & Jukka Tuohi. Otava.
Tammertekniikka: Tekniikan kaavasto tai Otava: MAOL-taulukot
In addition, online material prepared by the teacher, which is shared through the ItsLearning workspace.

Teaching methods

face-to-face teaching, task-based study, independent study, teamwork, virtual teaching

Exam schedules

1st sub-exam at week 44
2nd sub-exam at week 50
The possibility to repeat sub-exams is organized in December 2024 - January 2025 at a time to be announced later.

International connections

In the course, basic physics skills are studied, which are the basis of engineering work. The examples and tasks contain application examples related to the field of study. The course uses international physics notation and terminology, which gives students the skills to understand international engineering literature, standards, etc. When solving assignments, students are encouraged to work in a team. In the course an electrical learning environment is used.

Completion alternatives

If the student wants to complete the course with a test without homework, it must be agreed separately with the teacher.

Student workload

Contact lessons and exams 52 h
Independent study, homework and preparation for sub-exams 75 h

Content scheduling

9/2024 - 10/2024: Quantities, units, significant numbers, motion in one and two dimensions, projectile motion, free-body diagram, forces (Newton's laws), weight, forces of friction, work, energy and power; 1st sub-exam
11/2024 - 12/2024: Electrostatics (Coulomb's law, electric field and potential), DC circuits, circuit analysis, fundamentals of magnetism, induction, transformer, generator, AC, impedance, electromagnetic waves; 2nd sub-exam
12/2024 - 1/2025: Repeats of sub-exams.

Further information

The course requires a calculator (function calculator, graphing calculator or CAS-calculator).

As the lectures and homework sessions have topics where students work and answer questions in groups, the course requires minimum attendance of 50% of lectures and homework sessions. It does not affect grade, but only if one can pass the course.

(Avoin AMK 3 students)

Evaluation scale

H-5

Assessment methods and criteria

The course has a mandatory attendance which is 50% of lessons and homework session.
A maximum of 66 points for completing homework assignments (one point is awarded for each correctly solved assignment)
A maximum of 60 points from the sub-exams (2 x 30 points)

A total of at least 12 points must be obtained from the sub-exams.
At least 12 homeworks must be done from the area of sub-exam 1.
At least 10 homeworks must be done from area 2 of sub-exam.
However, a total of at least 50 points must be obtained.

The assessment is based on understanding the course content and sufficient training (homework).

Assessment criteria, fail (0)

Total less than 50 points.
or
A total of less than 12 points in the partial exams
or
Less than 12 homeworks have been done from the area of sub-exam 1.
or
Less than 10 homeworks have been done from area of sub-exam 2.
or
Attendance is less than 50%

Sufficient understanding of the course content has not been shown and there has been too little training.

Assessment criteria, satisfactory (1-2)

A total of at least 50 points and less than 74 points, and a total of at least 12 points from sub-exams and at least 12+10 points from homework.

The basics of the course content have been understood and enough training has been done.

Assessment criteria, good (3-4)

At least 74 points and less than 98 points and a total of at least 12 points from sub-exams and at least 12+10 points from homework.

The content of the course is mostly well understood and a reasonable amount of practice has been done.

Assessment criteria, excellent (5)

At least 98 points.

The content of the course is excellently understood and a lot of training has been done.

Qualifications

High school mathematics courses (higher or subsidiary level)
OR
Primary+secondary school and vocational school mathematics curriculum
OR
equivalent skills

Objective

After completing the course the student can:
- use quantities and units in accordance with the SI system
- solve problems consist of motion
- make graphical presentations and analyze them
- draw free-body diagram
- solve problems involved forces using Newton´s laws
- apply work and conservation of energy to solve problems
- calculate electric and magnetic forces acting on particles and the wave motion of an electro-magnetic fields in engineer’s work
- describe measurement techniques of temperature

Content

- SI system of units
- kinematics, friction
- Newton´s laws with some applications
- work, power and energy
- electric and magnetic fields

Evaluation scale

H-5

Qualifications

High school mathematics courses (higher or subsidiary level)
OR
Primary+secondary school and vocational school mathematics curriculum
OR
equivalent skills

Objective

After completing the course, the student
• can handle mathematical expressions and formulas within the engineering framework.
• understands the principles of solving equations and can solve equations encountered within technical applications.
• understands the basics of vector algebra and can apply vectors for modelling and solving technical problems.
• understands the basics concepts of geometry and trigonometry, and can apply them in modelling and problem solving.
• understands the concept of function and knows basic properties of functions.
• can apply functions for modelling and solving technical problems.
• understands the basic concepts of matrix algebra.
• can apply simultaneous equations for modelling and solving technical problems.
• can apply correct mathematical notations within the engineering framework.

Content

• Real numbers
• Basic arithmetic operations and the order of operations
• Algebraic expressions
• First and second order of polynomial equations and inequalities
• Simultaneous linear equations
• Radical functions and equations
• Exponential and logarithmic functions and equations
• Angles and angular units
• Right triangle and trigonometry
• Trigonometric functions and the unit circle
• Trigonometric equations
• The sine and cosine rules
• Basic concepts of vector algebra and modelling with vectors
• Scalar product and cross product of two vectors
• Basics of matrix algebra, determinant, inverse of a square matrix
• Field-specific content

Materials

- Luentomuistiinpanot sekä laskuharjoitusten tehtävät ja vastaukset OneNote-tiedostona
- Kaavakokoelma sekä opiskelijan oma MAOL/Tekniikan kaavasto
- Opiskelijan oma tavallinen funktiolaskin (ei graafinen/CAS/symbolinen/puhelin)

Teaching methods

Luennot
Laskuharjoitukset
Kokeet

Exam schedules

OSA1:
Osakoe1 ja sen uusinta lokakuussa
OSA2:
Osakoe2 ja sen uusinta joulukuussa

Lopullinen uusinta seuraavan vuoden tammikuussa:
voi tehdä jomman kumman tai kummatkin osakokeista, jos ei ole päässyt kurssista läpi.

Student workload

13*3h OSA1-luennot
2*2h kokeet
13*3h OSA2-luennot
2*2h kokeet
loppu opiskelijan itsenäistä opiskelua

Content scheduling

Syyskuu-lokakuu, OSA1:
- aritmetiikka
- algebra
- trigonometria

Lokakuu-joulukuu, OSA2:
- kompleksiluvut
- matriisilaskenta
- vektorilaskenta
- lukujärjestelmät

Further information

Sähköposti ja ITSL viestintäkanavina.

Evaluation scale

H-5

Assessment methods and criteria

Osakokeista täytyy saada 16/40 pistettä yhteensä päästäkseen läpi.
Laskuharjoituksista saatavat lisäpisteet parantavat arvosanaa, niitä voi saada max 10 pistettä.
Arvosanataulukko pisteiden mukaan:
0-15: 0
16-22: 1
23-29: 2
30-35: 3
36-42: 4
43-50: 5

Assessment criteria, fail (0)

Ei tarpeeksi pisteitä kokeista.

Assessment criteria, satisfactory (1-2)

Arvosanataulukon mukaan.

Assessment criteria, good (3-4)

Arvosanataulukon mukaan.

Assessment criteria, excellent (5)

Arvosanataulukon mukaan.

Qualifications

Introduction to mathematical sciences or corresponding skills.

Objective

After completing the course, the student
• can handle mathematical expressions and formulas within the engineering framework.
• understands the principles of solving equations and can solve equations encountered within technical applications.
• understands the basics of vector algebra and can apply vectors for modelling and solving technical problems.
• understands the basics concepts of geometry and trigonometry, and can apply them in modelling and problem solving.
• understands the concept of function and knows basic properties of functions.
• can apply functions for modelling and solving technical problems.
• understands the basic concepts of matrix algebra.
• can apply simultaneous equations for modelling and solving technical problems.
• can apply correct mathematical notations within the engineering framework.

Content

• Real numbers
• Basic arithmetic operations and the order of operations
• Algebraic expressions
• First and second order of polynomial equations and inequalities
• Simultaneous linear equations
• Radical functions and equations
• Exponential and logarithmic functions and equations
• Angles and angular units
• Right triangle and trigonometry
• Trigonometric functions and the unit circle
• Trigonometric equations
• The sine and cosine rules
• Basic concepts of vector algebra and modelling with vectors
• Scalar product and cross product of two vectors
• Basics of matrix algebra, determinant, inverse of a square matrix
• Field-specific content

Materials

Itslearning-sivulta löytyvät:
Luentomuistiinpanot
Kurssilla on käytössä kirja, josta on valtaosa tehtävistä: Insinöörin Matematiikka, Tuomenlehto, Holmlund, Huuskonen, Makkonen, Surakka.

Teaching methods

Luennot
Laskuharjoitukset
Kokeet

Exam schedules

Kurssilla pidetään kaksi osakoetta. Ensimmäinen osakoe on noin puolivälissä kurssia ja toinen kurssin lopussa. Kokeiden tarkat päivämäärät ilmoitetaan kurssin Itslearning alustalla.

Hylätyn kurssisuorituksen voi uusia uusintakokeella, joka pidetään toukokuussa.

Completion alternatives

Kurssilla ei ole vaihtoehtoisia suoritustapoja.

Student workload

26*2h luennot
13*2h laskuharjoitukset
2*2h kokeet
loppu opiskelijan itsenäistä opiskelua

Content scheduling

1. osa:
- trigonometria
- vektorit
- matriisit

2. osa:
- Lukujärjestelmät
- Kompleksiluvut
- Funktiot: polynomi, rationaali-, eksponentti- ja logaritmifunktiot
- 1. asteen yhtälö
- 2. asteen yhtälö
- yhtälöryhmät
- Epäyhtälö

Evaluation scale

H-5

Assessment methods and criteria

Osakokeiden yhteispistemäärästä täytyy saada 40% pisteistä päästäkseen kurssista läpi.
Laskuharjoituksista ja lähiopetuksen läsnäolosta saatavat lisäpisteet voivat parantavat arvosanaa.
Arvosanataulukko julkaistaan Itslearning alustalla

Assessment criteria, fail (0)

Hylätyn arvosanan kurssista saa, jos ei saavuta kurssinosakokeista minimi pistemäärää, joka on 40% osakokeiden yhteispistemäärästä.

Assessment criteria, satisfactory (1-2)

Arvosana määräytyy osakokeiden pistemäärän mukaisesti. Laskuharjoituksista ja lähiopetuksen läsnäolosta saatavat lisäpisteet voivat parantavat arvosanaa.

Assessment criteria, good (3-4)

Arvosana määräytyy osakokeiden pistemäärän mukaisesti. Laskuharjoituksista ja lähiopetuksen läsnäolosta saatavat lisäpisteet voivat parantavat arvosanaa.

Assessment criteria, excellent (5)

Arvosana määräytyy osakokeiden pistemäärän mukaisesti. Laskuharjoituksista ja lähiopetuksen läsnäolosta saatavat lisäpisteet voivat parantavat arvosanaa.

Qualifications

Introduction to mathematical sciences or corresponding skills.

Objective

The aim of the course is to activate and develop the students’ field-relevant English language and communication skills. The students will gain professional skills in various spoken and written communicative situations encountered in working life and society. In addition, they will learn to utilize tools and techniques to further develop their skills in authentic, field-specific contexts. More specifically, students will focus on developing their language and communication skills in.
Upon completing the course, the students should have acquired skills to communicate at level B2 according to European Framework of Reference for Languages, which states that at B2-level students should be able to produce clear, coherent and well-structured texts, present detailed descriptions related to one’s field of interest, express and exchange opinions using fluent language, follow complex arguments, and read longer articles and reports.

Content

- writing professional, field-specific texts
- presenting and discussing field-specific topics in a professional manner
- reading field-specific texts and utilizing the information in professional contexts
- learning and using key terminology of the field
- becoming professional, autonomous language users in working life

Materials

The course material is available in Its.

International connections

The course topics include sustainability with study on the key vocabulary, and discussion on the main aspects of sustainability.

Student workload

The students will work on contact meeting tasks, self-study tasks and be tested on their skills with spoken and written assignments on the course topics. The meeting tasks and assignments are completed during the contact meetings only. The self-study tasks are homework.

Content scheduling

The course will run from 2 September to 13 December.

The course consists of contact meetings (12x2h = 24h) and individual/group work in Its.

The course topics are professional emailing and reporting, meetings at work, and professional presentation. The topics include aspects of sustainability and/or digitalization, and field-specific vocabulary.

The aim of the course is to activate and develop the students’ field-relevant English language and communication skills. The students gain professional skills in various spoken and written communicative situations encountered in working life and society.

Learning objectives:

Spoken communication

The student
- presents topics in a structured way
- discusses topics using related terminology
- uses functional language e.g. signposting
- participates actively in discussions by commenting, asking, and reacting
- expresses themselves in a spontaneous way
- expresses themselves in a clear and logical way
- expresses themselves in their own words

Written communication

The student
- follows the structure and language of professional email and reporting
- recognizes and applies the appropriate style for the situation e.g. in terms of the vocabulary
- expresses themselves in a clear and logical way
- writes in their own words using sources correctly

Further information

The channel of communication during the course is Its.

Note that no general attendance is required but the assignments and meeting tasks are completed in contact meetings only (see evaluation).

Evaluation scale

H-5

Assessment methods and criteria

The evaluation is based on

1) four assignments

- email message, mini-report, meeting and presentation
- the evaluation scale for the assignments is 1-5
- specific evaluation criteria is given in connection with the instructions
- the average of individual assignment evaluations forms the final evaluation
- the assignments are completed in contact meetings only

2) meeting tasks and self-study tasks

- 8 tasks
- the evaluation scale is passed/failed
- if you return less than 6 tasks, the final evaluation will drop by one grade
- the meeting tasks are completed in contact meetings only

Points to be noted:

- For full final evaluation complete ALL course work within the given deadlines.
- Note that course work cannot be done again or replaced by other work, or an exam.
- With problems of completing course work, contact the teacher BEFORE the deadlines.
- Assignments are not accepted after 15 December 2024.

Objective

The aim of the course is to activate and develop the students’ field-relevant English language and communication skills. The students will gain professional skills in various spoken and written communicative situations encountered in working life and society. In addition, they will learn to utilize tools and techniques to further develop their skills in authentic, field-specific contexts. More specifically, students will focus on developing their language and communication skills in.
Upon completing the course, the students should have acquired skills to communicate at level B2 according to European Framework of Reference for Languages, which states that at B2-level students should be able to produce clear, coherent and well-structured texts, present detailed descriptions related to one’s field of interest, express and exchange opinions using fluent language, follow complex arguments, and read longer articles and reports.

Content

- writing professional, field-specific texts
- presenting and discussing field-specific topics in a professional manner
- reading field-specific texts and utilizing the information in professional contexts
- learning and using key terminology of the field
- becoming professional, autonomous language users in working life

Materials

The course material is available in Its.

International connections

The course topics include sustainability with study on the key vocabulary, and discussion on the main aspects of sustainability.

Student workload

The students will work on contact meeting tasks, self-study tasks and be tested on their skills with spoken and written assignments on the course topics. The meeting tasks and assignments are completed during the contact meetings only. The self-study tasks are homework.

Content scheduling

The course will run from 2 September to 13 December.

The course consists of contact meetings (12x2h = 24h) and individual/group work in Its.

The course topics are professional emailing and reporting, meetings at work, and professional presentation. The topics include aspects of sustainability and/or digitalization, and field-specific vocabulary.

The aim of the course is to activate and develop the students’ field-relevant English language and communication skills. The students gain professional skills in various spoken and written communicative situations encountered in working life and society.

Learning objectives:

Spoken communication

The student
- presents topics in a structured way
- discusses topics using related terminology
- uses functional language e.g. signposting
- participates actively in discussions by commenting, asking, and reacting
- expresses themselves in a spontaneous way
- expresses themselves in a clear and logical way
- expresses themselves in their own words

Written communication

The student
- follows the structure and language of professional email and reporting
- recognizes and applies the appropriate style for the situation e.g. in terms of the vocabulary
- expresses themselves in a clear and logical way
- writes in their own words using sources correctly

Further information

The channel of communication during the course is Its.

Note that no general attendance is required but the assignments and meeting tasks are completed in contact meetings only (see evaluation).

Evaluation scale

H-5

Assessment methods and criteria

The evaluation is based on

1) four assignments

- email message, mini-report, meeting and presentation
- the evaluation scale for the assignments is 1-5
- specific evaluation criteria is given in connection with the instructions
- the average of individual assignment evaluations forms the final evaluation
- the assignments are completed in contact meetings only

2) meeting tasks and self-study tasks

- 8 tasks
- the evaluation scale is passed/failed
- if you return less than 6 tasks, the final evaluation will drop by one grade
- the meeting tasks are completed in contact meetings only

Points to be noted:

- For full final evaluation complete ALL course work within the given deadlines.
- Note that course work cannot be done again or replaced by other work, or an exam.
- With problems of completing course work, contact the teacher BEFORE the deadlines.
- Assignments are not accepted after 15 December 2024.

Objective

The aim of the course is to activate and develop the students’ field-relevant English language and communication skills. The students will gain professional skills in various spoken and written communicative situations encountered in working life and society. In addition, they will learn to utilize tools and techniques to further develop their skills in authentic, field-specific contexts. More specifically, students will focus on developing their language and communication skills in.
Upon completing the course, the students should have acquired skills to communicate at level B2 according to European Framework of Reference for Languages, which states that at B2-level students should be able to produce clear, coherent and well-structured texts, present detailed descriptions related to one’s field of interest, express and exchange opinions using fluent language, follow complex arguments, and read longer articles and reports.

Content

- writing professional, field-specific texts
- presenting and discussing field-specific topics in a professional manner
- reading field-specific texts and utilizing the information in professional contexts
- learning and using key terminology of the field
- becoming professional, autonomous language users in working life

Materials

The channel of communication during the course is Its.

Note that no general attendance is required but the assignments and meeting tasks are completed in contact meetings only (see evaluation).

International connections

The course topics include sustainability with study on the key vocabulary, and discussion on the main aspects of sustainability.

Completion alternatives

The course material is available in Its.

Student workload

The students will work on contact meeting tasks, self-study tasks and be tested on their skills with spoken and written assignments on the course topics. The meeting tasks and assignments are completed during the contact meetings only. The self-study tasks are homework.

Content scheduling

The course will run from 2 September to 13 December.

The course consists of contact meetings (12x2h = 24h) and individual/group work in Its.

The course topics are professional emailing and reporting, meetings at work, and professional presentation. The topics include aspects of sustainability and/or digitalization, and field-specific vocabulary.

The aim of the course is to activate and develop the students’ field-relevant English language and communication skills. The students gain professional skills in various spoken and written communicative situations encountered in working life and society.

Learning objectives:

Spoken communication

The student
- presents topics in a structured way
- discusses topics using related terminology
- uses functional language e.g. signposting
- participates actively in discussions by commenting, asking, and reacting
- expresses themselves in a spontaneous way
- expresses themselves in a clear and logical way
- expresses themselves in their own words

Written communication

The student
- follows the structure and language of professional email and reporting
- recognizes and applies the appropriate style for the situation e.g. in terms of the vocabulary
- expresses themselves in a clear and logical way
- writes in their own words using sources correctly

Evaluation scale

H-5

Assessment methods and criteria

The evaluation is based on

1) four assignments

- email message, mini-report, meeting and presentation
- the evaluation scale for the assignments is 1-5
- specific evaluation criteria is given in connection with the instructions
- the average of individual assignment evaluations forms the final evaluation
- the assignments are completed in contact meetings only

2) meeting tasks and self-study tasks

- 8 tasks
- the evaluation scale is passed/failed
- if you return less than 6 tasks, the final evaluation will drop by one grade
- the meeting tasks are completed in contact meetings only

Points to be noted:

- For full final evaluation complete ALL course work within the given deadlines.
- Note that course work cannot be done again or replaced by other work, or an exam.
- With problems of completing course work, contact the teacher BEFORE the deadlines.
- Assignments are not accepted after 15 December 2024.

Objective

The aim of the course is to activate and develop the students’ field-relevant English language and communication skills. The students will gain professional skills in various spoken and written communicative situations encountered in working life and society. In addition, they will learn to utilize tools and techniques to further develop their skills in authentic, field-specific contexts. More specifically, students will focus on developing their language and communication skills in.
Upon completing the course, the students should have acquired skills to communicate at level B2 according to European Framework of Reference for Languages, which states that at B2-level students should be able to produce clear, coherent and well-structured texts, present detailed descriptions related to one’s field of interest, express and exchange opinions using fluent language, follow complex arguments, and read longer articles and reports.

Content

- writing professional, field-specific texts
- presenting and discussing field-specific topics in a professional manner
- reading field-specific texts and utilizing the information in professional contexts
- learning and using key terminology of the field
- becoming professional, autonomous language users in working life

Evaluation scale

H-5

Objective

The aim of the course is to activate and develop the students’ field-relevant English language and communication skills. The students will gain professional skills in various spoken and written communicative situations encountered in working life and society. In addition, they will learn to utilize tools and techniques to further develop their skills in authentic, field-specific contexts. More specifically, students will focus on developing their language and communication skills in.
Upon completing the course, the students should have acquired skills to communicate at level B2 according to European Framework of Reference for Languages, which states that at B2-level students should be able to produce clear, coherent and well-structured texts, present detailed descriptions related to one’s field of interest, express and exchange opinions using fluent language, follow complex arguments, and read longer articles and reports.

Content

- writing professional, field-specific texts
- presenting and discussing field-specific topics in a professional manner
- reading field-specific texts and utilizing the information in professional contexts
- learning and using key terminology of the field
- becoming professional, autonomous language users in working life

Materials

teacher’s own and web-based material

Teaching methods

teacher-directed classroom activities, independent work, pair work, group work, project work, online activities (quizzes, meetings)

Exam schedules

No exam. There is continuous assessment.

International connections

The contents and the assessed outputs of the course are designed to provide the students with English language communication skills they need in working life especially when working in projects. Examples include producing instructions and reports, organizing physical and online meetings and producing the relevant documents and emails, collaborative writing and presentation of results. In addition, the students have to complete tasks individually, in pairs and as a group which enhances their communication and interpersonal skills. The assessment is continuous and teacher and peer assessment is provided after the completion of each task.
The course deals with the theme of sustainable development in discussing presenting, reading articles about general concepts ( e.g. green IT, energy efficiency), technologies & strategies (such as cloud computing, virtualization); social & ethical issues ( e.g. data privacy, digital divide, inclusive access)

Completion alternatives

A: The student can complete the English Professional Skills B2 (5ECTS) and complete Accreditation of Prior Learning based on Competence (not transfer of credits):
Within two weeks since the course start, the student submits a video and a written report showcasing expertise in oral and written workplace communication and professional communication. The report must include concrete examples of workplace communication (e.g. meetings, negotiations, written reports, instructions, emails, and so on). If the submission fulfills the assessment criteria, the student can attain the credits. If the submission does not meet the criteria, the student joins the course.
B: The student can complete the English Professional Skills B2 (5ECTS) and complete Transfer of Credits within the first two weeks of the course if the student has completed a course with the same credits and similar content at a same level (higher education)) educational institution within the last 5 years. The student will also need to provide an official transcript and course content description. Please note that this method of attainment does not apply to Open Path students

Student workload

classroom activities: 28 h
individual work: 45 h
pairwork work: 30 h
group work: 27h

Content scheduling

January – April 2025
1. Before you start
2. Introducing yourself & studies
3. Emails
4. Presentations
5. Reporting
6. Meetings
7. End of course evaluation

Evaluation scale

H-5

Assessment methods and criteria

The students need to physically attend and complete all the tasks/assignments within the deadlines in order to pass the course because this improves the student's ability to track their own learning, receive continuous feedback, and provide ongoing evidence of their skill development throughout the course.

Assessment criteria, fail (0)

The student has insufficient attendance (has been absent in more than 4 classes). The student has not completed all the tasks. The student has completed tasks but they are not of an acceptable standard. The student has a high percentage (over 15% of similarity in written assignments)

Assessment criteria, satisfactory (1-2)

The student has completed the tasks with the minimum of set requirements which are outlined by the teacher and are listed in the task instructions. The student has completed tasks later than the given deadlines. The student has not addressed feedback provided by the teacher. The student has been superficially reflecting on his/her own performance and has been late or reluctant to give peer feedback.

Assessment criteria, good (3-4)

The student has completed the tasks well fulfilling most of the set requirements which are outlined by the teachers and are listed in the task instructions. The student has completed tasks within the given deadlines. The student has partly addressed feedback provided by the teacher. The student has been reflecting on his/her own performance and has been giving peer feedback.

Assessment criteria, excellent (5)

The student has completed the tasks very well fulfilling or surpassing the set requirements which are outlined by the teachers and are listed in the task instructions. The student has completed tasks within the given deadlines or earlier and has addressed well feedback provided by the teacher. The student has been critically reflecting on his/her own performance and has been giving quality peer feedback.

Objective

The aim of the course is to activate and develop the students’ field-relevant English language and communication skills. The students will gain professional skills in various spoken and written communicative situations encountered in working life and society. In addition, they will learn to utilize tools and techniques to further develop their skills in authentic, field-specific contexts. More specifically, students will focus on developing their language and communication skills in.
Upon completing the course, the students should have acquired skills to communicate at level B2 according to European Framework of Reference for Languages, which states that at B2-level students should be able to produce clear, coherent and well-structured texts, present detailed descriptions related to one’s field of interest, express and exchange opinions using fluent language, follow complex arguments, and read longer articles and reports.

Content

- writing professional, field-specific texts
- presenting and discussing field-specific topics in a professional manner
- reading field-specific texts and utilizing the information in professional contexts
- learning and using key terminology of the field
- becoming professional, autonomous language users in working life

Materials

teacher’s own and web-based material

Teaching methods

teacher-directed classroom activities, independent work, pair work, group work, project work, online activities (quizzes, meetings)

Exam schedules

No exam. There is continuous assessment.

International connections

The contents and the assessed outputs of the course are designed to provide the students with English language communication skills they need in working life especially when working in projects. Examples include producing instructions and reports, organizing physical and online meetings and producing the relevant documents and emails, collaborative writing and presentation of results. In addition, the students have to complete tasks individually, in pairs and as a group which enhances their communication and interpersonal skills. The assessment is continuous and teacher and peer assessment is provided after the completion of each task.
The course deals with the theme of sustainable development in discussing presenting, reading articles about general concepts ( e.g. green IT, energy efficiency), technologies & strategies (such as cloud computing, virtualization); social & ethical issues ( e.g. data privacy, digital divide, inclusive access)

Completion alternatives

A: The student can complete the English Professional Skills B2 (5ECTS) and complete Accreditation of Prior Learning based on Competence (not transfer of credits):
Within two weeks since the course start, the student submits a video and a written report showcasing expertise in oral and written workplace communication and professional communication. The report must include concrete examples of workplace communication (e.g. meetings, negotiations, written reports, instructions, emails, and so on). If the submission fulfills the assessment criteria, the student can attain the credits. If the submission does not meet the criteria, the student joins the course.
B: The student can complete the English Professional Skills B2 (5ECTS) and complete Transfer of Credits within the first two weeks of the course if the student has completed a course with the same credits and similar content at a same level (higher education)) educational institution within the last 5 years. The student will also need to provide an official transcript and course content description. Please note that this method of attainment does not apply to Open Path students

Student workload

classroom activities: 28 h
individual work: 45 h
pairwork work: 30 h
group work: 27h

Content scheduling

January – April 2025
1. Before you start
2. Introducing yourself & studies
3. Emails
4. Presentations
5. Reporting
6. Meetings
7. End of course evaluation

Evaluation scale

H-5

Assessment methods and criteria

The students need to physically attend and complete all the tasks/assignments within the deadlines in order to pass the course because this improves the student's ability to track their own learning, receive continuous feedback, and provide ongoing evidence of their skill development throughout the course.

Assessment criteria, fail (0)

The student has insufficient attendance (has been absent in more than 4 classes). The student has not completed all the tasks. The student has completed tasks but they are not of an acceptable standard. The student has a high percentage (over 15% of similarity in written assignments)

Assessment criteria, satisfactory (1-2)

The student has completed the tasks with the minimum of set requirements which are outlined by the teacher and are listed in the task instructions. The student has completed tasks later than the given deadlines. The student has not addressed feedback provided by the teacher. The student has been superficially reflecting on his/her own performance and has been late or reluctant to give peer feedback.

Assessment criteria, good (3-4)

The student has completed the tasks well fulfilling most of the set requirements which are outlined by the teachers and are listed in the task instructions. The student has completed tasks within the given deadlines. The student has partly addressed feedback provided by the teacher. The student has been reflecting on his/her own performance and has been giving peer feedback.

Assessment criteria, excellent (5)

The student has completed the tasks very well fulfilling or surpassing the set requirements which are outlined by the teachers and are listed in the task instructions. The student has completed tasks within the given deadlines or earlier and has addressed well feedback provided by the teacher. The student has been critically reflecting on his/her own performance and has been giving quality peer feedback.

Objective

By the end of this course, students will be able:

· Configure single-area OSPFv2 in both point-to-point and multiaccess networks.
· Explain how to mitigate threats and enhance network security using access control lists and security best practices.
· Implement standard IPv4 ACLs to filter traffic and secure administrative access.
· Configure NAT services on the edge router to provide IPv4 address scalability.
· Explain techniques to provide address scalability and secure remote access for WANs.
· Explain how to optimize, monitor, and troubleshoot scalable network architectures.
· Explain how networking devices implement QoS.
· Implement protocols to manage the network.
· Explain how technologies such as virtualization, software defined networking, and automation affect evolving networks.

Content

Enterprise Networking, Security, and Automation (ENSA) describes the architecture, components, operations, and security to scale for large, complex networks, including wide area network (WAN) technologies. The course emphasizes network security concepts and introduces network virtualization and automation. Students learn how to configure, troubleshoot, and secure enterprise network devices and understand how application programming interfaces (API) and configuration management tools enable network automation. The course includes activities using Packet Tracer, hands-on lab work, and a wide array of assessment types and tools.

Materials

All needed material will be available online in https://www.netacad.com
Further course enrollment instructions are provided by instructor.
Please register to the site using school email.

Exam schedules

Theory final exam and Packet Tracer exam will held in course.
You can do one re-exam within course deadline.
NOTE: Course ending time shown in academy system is not real, please check the course plan for end date!

Student workload

Lecturing and laboratory work each week
Independent studying, including:

- Studying the course material
- Completing exercises
- Preparation for finals exam(s)

Content scheduling

Course describes the architecture, components, operations, and security to scale for large, complex networks, including wide area network (WAN) technologies. The course emphasizes network security concepts and introduces network virtualization and automation. Students learn how to configure, troubleshoot, and secure enterprise network devices and understand how application programming interfaces (API) and configuration management tools enable network automation.

By the end of this course, students will be able:

- Configure single-area OSPFv2 in both point-to-point and multiaccess networks.
- Explain how to mitigate threats and enhance network security using access control lists and security best practices.
- Implement standard IPv4 ACLs to filter traffic and secure administrative access.
- Configure NAT services on the edge router to provide IPv4 address scalability.
- Explain techniques to provide address scalability and secure remote access for WANs.
- Explain how to optimize, monitor, and troubleshoot scalable network architectures.
- Explain how networking devices implement QoS.
- Implement protocols to manage the network.
- Explain how technologies such as virtualization, software defined networking, and automation affect evolving networks.

Evaluation scale

H-5

Assessment methods and criteria

Laboratory assignments in laboratory room
Packet tracer assignments done at home
Module exams
Practice final exams
Theory final exam and Packet Tracer final exam.


The overall result is the sum of the all results of the assignments and exams, passing limit is 60%.
Detailed grading limits will be provided in course plan when course starts but past grading limits have been the following:

Less than 60% Fail
60-67.4% Grade 1
68-75.4% Grade 2
76-83.4% Grade 3
84-91.4% Grade 4
91.5% or higher Grade 5

Qualifications

Courses Internet Networks and Security (5051215) and Introduction to Networks (TE00BU42) ,or equivalent skills.

Objective

In the studies of the Finnish language and communication, you will become familiar with expert and workplace communication. During this course, you will practice communication and interaction skills required in the professional world.

After completing the course, you will be able to:
• operate in communication and interaction situations in your own field
• develop your own communication skills
• consider the recipient, the situation, and the practices of your professional field.

Content

Course content:
- Characteristics of professional communication style
- Analysis and writing of field-specific texts
- Workplace oral communication situations
- Self-assessment of communication skills
- Giving and receiving feedback

Materials

Verkkomateriaali ja opettajan materiaali, jotka jaetaan ItsLearningin kautta.
Mahdollisesti Kauppinen, A.; Nummi, J. & Savola, T. (2012 tai uud.). Tekniikan viestintä. Kirjoittamisen ja puhumisen käsikirja. Helsinki: Edita.

Teaching methods

kontaktiopetus laboratoriotyyppisesti, tehtäväperustaisuus, itsenäinen opiskelu, tiimityö
Suuri osa tehtävistä on mahdollista tehdä vain osallistumalla kontaktiopetukseen, joten läsnäolo tunneilla on tärkeää.

Exam schedules

Opintojaksolla ei ole tenttiä, vaan arviointi perustuu osatehtäviin ja jatkuvaan arviointiin.

International connections

Opintojaksolla opiskellaan laboratoriomaisesti viestinnän ja vuorovaikutuksen perustaitoja, jotka harjaannuttavat oman alan työtehtävissä tarvittaviin vuorovaikutus- ja viestintätaitoihin. Opiskelija tutustuu ennen kontaktitunteja kontaktitunnin aiheisiin, joihin on annettu materiaaleja ja linkkejä Itslearningissa. Opintojaksolla tehtäviä ryhmäharjoituksia tehdään erikokoisissa ja vaihtuvissa pienryhmissä, joissa asiaosaamisen lisäksi harjoitellaan mm. vuorovaikutustaitoja, keskustelu- ja esiintymistaitoja, yhteiskirjoittamisen taitoja, vertaispalautteen antamista suullisesti ja kirjallisesti. Yksilötehtävissä kehitetään yksilöllisiä viestintävalmiuksia. Opintojaksolla käytetään monipuolisesti digitaalista opiskelumateriaalia ja sähköistä oppimisympäristöä videoiden ja tekstien palauttamiseen sekä materiaalin jakamiseen.

Completion alternatives

Ei ole vaillinaista suoritustapaa.

Student workload

Opiskelijan työmäärä koostuu kontaktitunneista (n. 36 t), kotitehtävistä ja itsenäisestä opiskelusta, ennakkotehtävistä, itsenäisestä materiaaliin tutustumisesta ym. (n. 34 t), asiatyylisen tekstin laatimisesta (n. 20 t), puhe-esitykseen valmistautumisesta (n. 20 t) ja kielenhuollon testiin valmistautumisesta (n. 20 t).

Content scheduling

syys–joulukuu 2024
asiantuntija viestijänä, puhe-esityksen valmistautuminen, puhe-esityksiä, asiatyylinen kirjoittaminen ja harjoituksia

Opintojakson tavoitteet, tehtävät ja niiden arviointi, aikataulutus yms. käytännön asiat käydään läpi ensimmäisellä tapaamiskerralla, jolloin opiskelijan on syytä olla paikalla. Ellei opiskelija ole ensimmäisellä kerralla paikalla, on hänen selvitettävä itse opintojakson ensimmäisellä tunnilla käydyt asiat Itslearningin materiaaleista ja Pepistä.

Further information

Participating in the study course is required to have Finnish language skills from the mother tongue level, i.e. C skill level. It is the student's responsibility to check that the prerequisite conditions are met before registering. The teacher has grounds to reject the registration if the prerequisites are not met.

Opintojaksolle osallistuvalta edellytetään äidinkielen tasoista suomen kielen taitoa eli C-taitotasoa. Opiskelijalla on vastuu tarkistaa edeltävyysehtojen täyttyminen ennen ilmoittautumista. Opettajalla on peruste hylätä ilmoittautuminen, jos edeltävyysehdot eivät täyty.

Viestintäkanavana käytetään sähköpostia ja Itslearningia.

Evaluation scale

H-5

Assessment methods and criteria

Arviointi perustuu osatehtäviin ja jatkuvaan arviointiin.
Arvosana muodostuu seuraavasti:
asiatyylinen teksti 25 %
kielenhuollon testi 25 %
suullinen esitys 25 %
tunti- ja kotitehtävät 25 %

Kuhunkin tehtävään liittyvät arviointikriteerit kerrotaan tarkemmin tehtävänannon yhteydessä. Tehtävien palautusajat ovat ehdottomia, myöhästyneitä tehtäviä ei oteta vastaan.
Opiskelijan ilmoittautuminen opintojaksolle poistetaan viimeistään kuukauden kuluttua, ellei ole näyttöä aikomuksesta suorittaa opintojakso.

Assessment criteria, fail (0)

The Finnish language skills of the student participating in the course do not meet the C skill level requirements.

Opiskelija on osallistunut ryhmän työskentelyyn vain vähän tai ei ollenkaan ja/tai ns. tunti-/kotitehtävistä saatu pistemäärä on kokonaisarvioinnissa alle 1 p.

Opiskelija ei ole suorittanut oppimistehtäviä hyväksytysti tai saavuttanut hyväksyttyyn arvosanaan oikeuttavaa pistemäärää oppimistehtävistä..

Opiskelijan ilmoittautuminen opintojaksolle poistetaan viimeistään kuukauden kuluttua, jos hänellä ei ole näyttöä aikomuksesta suorittaa opintojakso.

Assessment criteria, satisfactory (1-2)

Opiskelija pystyy kirjoittamaan asiatyylisen, ohjeiden mukaisen lähdemateriaaliin pohjautuvan raportin. Opiskelija tunnistaa kielenhuollon merkityksen asiatekstissä. Opiskelija pystyy pitämään suullisen esityksen. Hän osallistuu lähitapaamisiin ja keskusteluun osittain.

Assessment criteria, good (3-4)

Opiskelija tietää, mikä on viestinnän merkitys työyhteisössä. Hän pystyy kirjoittamaan ohjeiden mukaisen ja teoriakirjallisuutta hyvin hyödyntävän raportin. Opiskelija osoittaa kielenhuollon tuntemusta. Opiskelija pitää suullisen esityksen ohjeiden mukaisesti. Opiskelija asennoituu viestintään positiivisesti sekä osallistuu lähitapaamisten työskentelyyn ja keskusteluun aktiivisesti.

Assessment criteria, excellent (5)

Opiskelija tietää ja ymmärtää, mikä on viestinnän merkitys työyhteisössä ja innostuu pohtimaan viestintää käytännössä esimerkiksi omassa työskentelyssään. Hän pystyy suunnittelemaan ja kirjoittamaan ohjeiden mukaisen ja erinomaisella tavalla teoriakirjallisuutta hyödyntävän raportin. Opiskelija osaa arvioida kielenhuollon osaamistaan ja käyttää tietoperustaa tekstinsä tarkistamisessa. Opiskelija pitää suullisen esityksen ohjeiden mukaisesti ja osaa soveltaa ohjeita ja kokemuksiaan esitykseensä. Opiskelija asennoituu viestintään erittäin positiivisesti sekä osallistuu lähitapaamisten työskentelyyn ja keskusteluun motivoituneena ja tavoitteellisesti.

Qualifications

Participation in the course requires a language proficiency level of C in Finnish.

Objective

In the studies of the Finnish language and communication, you will become familiar with expert and workplace communication. During this course, you will practice communication and interaction skills required in the professional world.

After completing the course, you will be able to:
• operate in communication and interaction situations in your own field
• develop your own communication skills
• consider the recipient, the situation, and the practices of your professional field.

Content

Course content:
- Characteristics of professional communication style
- Analysis and writing of field-specific texts
- Workplace oral communication situations
- Self-assessment of communication skills
- Giving and receiving feedback

Materials

Verkkomateriaali ja opettajan materiaali, jotka jaetaan ItsLearningin kautta.
Mahdollisesti Kauppinen, A.; Nummi, J. & Savola, T. (2012 tai uud.). Tekniikan viestintä. Kirjoittamisen ja puhumisen käsikirja. Helsinki: Edita.

Teaching methods

kontaktiopetus laboratoriotyyppisesti, tehtäväperustaisuus, itsenäinen opiskelu, tiimityö
Suuri osa tehtävistä on mahdollista tehdä vain osallistumalla kontaktiopetukseen, joten läsnäolo tunneilla on tärkeää.

Exam schedules

Opintojaksolla ei ole tenttiä, vaan arviointi perustuu osatehtäviin ja jatkuvaan arviointiin.

International connections

Opintojaksolla opiskellaan laboratoriomaisesti viestinnän ja vuorovaikutuksen perustaitoja, jotka harjaannuttavat oman alan työtehtävissä tarvittaviin vuorovaikutus- ja viestintätaitoihin. Opiskelija tutustuu ennen kontaktitunteja kontaktitunnin aiheisiin, joihin on annettu materiaaleja ja linkkejä Itslearningissa. Opintojaksolla tehtäviä ryhmäharjoituksia tehdään erikokoisissa ja vaihtuvissa pienryhmissä, joissa asiaosaamisen lisäksi harjoitellaan mm. vuorovaikutustaitoja, keskustelu- ja esiintymistaitoja, yhteiskirjoittamisen taitoja, vertaispalautteen antamista suullisesti ja kirjallisesti. Yksilötehtävissä kehitetään yksilöllisiä viestintävalmiuksia. Opintojaksolla käytetään monipuolisesti digitaalista opiskelumateriaalia ja sähköistä oppimisympäristöä videoiden ja tekstien palauttamiseen sekä materiaalin jakamiseen.

Completion alternatives

Ei ole vaillinaista suoritustapaa.

Student workload

Opiskelijan työmäärä koostuu kontaktitunneista (n. 36 t), kotitehtävistä ja itsenäisestä opiskelusta, ennakkotehtävistä, itsenäisestä materiaaliin tutustumisesta ym. (n. 34 t), asiatyylisen tekstin laatimisesta (n. 20 t), puhe-esitykseen valmistautumisesta (n. 20 t) ja kielenhuollon testiin valmistautumisesta (n. 20 t).

Content scheduling

syys–joulukuu 2024
asiantuntija viestijänä, puhe-esityksen valmistautuminen, puhe-esityksiä, asiatyylinen kirjoittaminen ja harjoituksia

Opintojakson tavoitteet, tehtävät ja niiden arviointi, aikataulutus yms. käytännön asiat käydään läpi ensimmäisellä tapaamiskerralla, jolloin opiskelijan on syytä olla paikalla. Ellei opiskelija ole ensimmäisellä kerralla paikalla, on hänen selvitettävä itse opintojakson ensimmäisellä tunnilla käydyt asiat Itslearningin materiaaleista ja Pepistä.

Further information

Participating in the study course is required to have Finnish language skills from the mother tongue level, i.e. C skill level. It is the student's responsibility to check that the prerequisite conditions are met before registering. The teacher has grounds to reject the registration if the prerequisites are not met.

Opintojaksolle osallistuvalta edellytetään äidinkielen tasoista suomen kielen taitoa eli C-taitotasoa. Opiskelijalla on vastuu tarkistaa edeltävyysehtojen täyttyminen ennen ilmoittautumista. Opettajalla on peruste hylätä ilmoittautuminen, jos edeltävyysehdot eivät täyty.

Viestintäkanavana käytetään sähköpostia ja Itslearningia.

Evaluation scale

H-5

Assessment methods and criteria

Arviointi perustuu osatehtäviin ja jatkuvaan arviointiin.
Arvosana muodostuu seuraavasti:
asiatyylinen teksti 25 %
kielenhuollon testi 25 %
suullinen esitys 25 %
tunti- ja kotitehtävät 25 %

Kuhunkin tehtävään liittyvät arviointikriteerit kerrotaan tarkemmin tehtävänannon yhteydessä. Tehtävien palautusajat ovat ehdottomia, myöhästyneitä tehtäviä ei oteta vastaan.
Opiskelijan ilmoittautuminen opintojaksolle poistetaan viimeistään kuukauden kuluttua, ellei ole näyttöä aikomuksesta suorittaa opintojakso.

Assessment criteria, fail (0)

The Finnish language skills of the student participating in the course do not meet the C skill level requirements.

Opiskelija on osallistunut ryhmän työskentelyyn vain vähän tai ei ollenkaan ja/tai ns. tunti-/kotitehtävistä saatu pistemäärä on kokonaisarvioinnissa alle 1 p.

Opiskelija ei ole suorittanut oppimistehtäviä hyväksytysti tai saavuttanut hyväksyttyyn arvosanaan oikeuttavaa pistemäärää oppimistehtävistä..

Opiskelijan ilmoittautuminen opintojaksolle poistetaan viimeistään kuukauden kuluttua, jos hänellä ei ole näyttöä aikomuksesta suorittaa opintojakso.

Assessment criteria, satisfactory (1-2)

Opiskelija pystyy kirjoittamaan asiatyylisen, ohjeiden mukaisen lähdemateriaaliin pohjautuvan raportin. Opiskelija tunnistaa kielenhuollon merkityksen asiatekstissä. Opiskelija pystyy pitämään suullisen esityksen. Hän osallistuu lähitapaamisiin ja keskusteluun osittain.

Assessment criteria, good (3-4)

Opiskelija tietää, mikä on viestinnän merkitys työyhteisössä. Hän pystyy kirjoittamaan ohjeiden mukaisen ja teoriakirjallisuutta hyvin hyödyntävän raportin. Opiskelija osoittaa kielenhuollon tuntemusta. Opiskelija pitää suullisen esityksen ohjeiden mukaisesti. Opiskelija asennoituu viestintään positiivisesti sekä osallistuu lähitapaamisten työskentelyyn ja keskusteluun aktiivisesti.

Assessment criteria, excellent (5)

Opiskelija tietää ja ymmärtää, mikä on viestinnän merkitys työyhteisössä ja innostuu pohtimaan viestintää käytännössä esimerkiksi omassa työskentelyssään. Hän pystyy suunnittelemaan ja kirjoittamaan ohjeiden mukaisen ja erinomaisella tavalla teoriakirjallisuutta hyödyntävän raportin. Opiskelija osaa arvioida kielenhuollon osaamistaan ja käyttää tietoperustaa tekstinsä tarkistamisessa. Opiskelija pitää suullisen esityksen ohjeiden mukaisesti ja osaa soveltaa ohjeita ja kokemuksiaan esitykseensä. Opiskelija asennoituu viestintään erittäin positiivisesti sekä osallistuu lähitapaamisten työskentelyyn ja keskusteluun motivoituneena ja tavoitteellisesti.

Qualifications

Participation in the course requires a language proficiency level of C in Finnish.

Objective

In the studies of the Finnish language and communication, you will become familiar with expert and workplace communication. During this course, you will practice communication and interaction skills required in the professional world.

After completing the course, you will be able to:
• operate in communication and interaction situations in your own field
• develop your own communication skills
• consider the recipient, the situation, and the practices of your professional field.

Content

Course content:
- Characteristics of professional communication style
- Analysis and writing of field-specific texts
- Workplace oral communication situations
- Self-assessment of communication skills
- Giving and receiving feedback

Materials

Verkkomateriaali ja opettajan materiaali, jotka jaetaan ItsLearningin kautta.
Mahdollisesti Kauppinen, A.; Nummi, J. & Savola, T. (2012 tai uud.). Tekniikan viestintä. Kirjoittamisen ja puhumisen käsikirja. Helsinki: Edita.

Teaching methods

kontaktiopetus laboratoriotyyppisesti, tehtäväperustaisuus, itsenäinen opiskelu, tiimityö
Suuri osa tehtävistä on mahdollista tehdä vain osallistumalla kontaktiopetukseen, joten läsnäolo tunneilla on tärkeää.

Exam schedules

Opintojaksolla ei ole tenttiä, vaan arviointi perustuu osatehtäviin ja jatkuvaan arviointiin.

International connections

Opintojaksolla opiskellaan laboratoriomaisesti viestinnän ja vuorovaikutuksen perustaitoja, jotka harjaannuttavat oman alan työtehtävissä tarvittaviin vuorovaikutus- ja viestintätaitoihin. Opiskelija tutustuu ennen kontaktitunteja kontaktitunnin aiheisiin, joihin on annettu materiaaleja ja linkkejä Itslearningissa. Opintojaksolla tehtäviä ryhmäharjoituksia tehdään erikokoisissa ja vaihtuvissa pienryhmissä, joissa asiaosaamisen lisäksi harjoitellaan mm. vuorovaikutustaitoja, keskustelu- ja esiintymistaitoja, yhteiskirjoittamisen taitoja, vertaispalautteen antamista suullisesti ja kirjallisesti. Yksilötehtävissä kehitetään yksilöllisiä viestintävalmiuksia. Opintojaksolla käytetään monipuolisesti digitaalista opiskelumateriaalia ja sähköistä oppimisympäristöä videoiden ja tekstien palauttamiseen sekä materiaalin jakamiseen.

Completion alternatives

Ei ole vaillinaista suoritustapaa.

Student workload

Opiskelijan työmäärä koostuu kontaktitunneista (n. 36 t), kotitehtävistä ja itsenäisestä opiskelusta, ennakkotehtävistä, itsenäisestä materiaaliin tutustumisesta ym. (n. 34 t), asiatyylisen tekstin laatimisesta (n. 20 t), puhe-esitykseen valmistautumisesta (n. 20 t) ja kielenhuollon testiin valmistautumisesta (n. 20 t).

Content scheduling

syys–joulukuu 2024
asiantuntija viestijänä, puhe-esityksen valmistautuminen, puhe-esityksiä, asiatyylinen kirjoittaminen ja harjoituksia

Opintojakson tavoitteet, tehtävät ja niiden arviointi, aikataulutus yms. käytännön asiat käydään läpi ensimmäisellä tapaamiskerralla, jolloin opiskelijan on syytä olla paikalla. Ellei opiskelija ole ensimmäisellä kerralla paikalla, on hänen selvitettävä itse opintojakson ensimmäisellä tunnilla käydyt asiat Itslearningin materiaaleista ja Pepistä.

Further information

Participating in the study course is required to have Finnish language skills from the mother tongue level, i.e. C skill level. It is the student's responsibility to check that the prerequisite conditions are met before registering. The teacher has grounds to reject the registration if the prerequisites are not met.

Opintojaksolle osallistuvalta edellytetään äidinkielen tasoista suomen kielen taitoa eli C-taitotasoa. Opiskelijalla on vastuu tarkistaa edeltävyysehtojen täyttyminen ennen ilmoittautumista. Opettajalla on peruste hylätä ilmoittautuminen, jos edeltävyysehdot eivät täyty.

Viestintäkanavana käytetään sähköpostia ja Itslearningia.

Evaluation scale

H-5

Assessment methods and criteria

Arviointi perustuu osatehtäviin ja jatkuvaan arviointiin.
Arvosana muodostuu seuraavasti:
asiatyylinen teksti 25 %
kielenhuollon testi 25 %
suullinen esitys 25 %
tunti- ja kotitehtävät 25 %

Kuhunkin tehtävään liittyvät arviointikriteerit kerrotaan tarkemmin tehtävänannon yhteydessä. Tehtävien palautusajat ovat ehdottomia, myöhästyneitä tehtäviä ei oteta vastaan.
Opiskelijan ilmoittautuminen opintojaksolle poistetaan viimeistään kuukauden kuluttua, ellei ole näyttöä aikomuksesta suorittaa opintojakso.

Assessment criteria, fail (0)

The Finnish language skills of the student participating in the course do not meet the C skill level requirements.

Opiskelija on osallistunut ryhmän työskentelyyn vain vähän tai ei ollenkaan ja/tai ns. tunti-/kotitehtävistä saatu pistemäärä on kokonaisarvioinnissa alle 1 p.

Opiskelija ei ole suorittanut oppimistehtäviä hyväksytysti tai saavuttanut hyväksyttyyn arvosanaan oikeuttavaa pistemäärää oppimistehtävistä..

Opiskelijan ilmoittautuminen opintojaksolle poistetaan viimeistään kuukauden kuluttua, jos hänellä ei ole näyttöä aikomuksesta suorittaa opintojakso.

Assessment criteria, satisfactory (1-2)

Opiskelija pystyy kirjoittamaan asiatyylisen, ohjeiden mukaisen lähdemateriaaliin pohjautuvan raportin. Opiskelija tunnistaa kielenhuollon merkityksen asiatekstissä. Opiskelija pystyy pitämään suullisen esityksen. Hän osallistuu lähitapaamisiin ja keskusteluun osittain.

Assessment criteria, good (3-4)

Opiskelija tietää, mikä on viestinnän merkitys työyhteisössä. Hän pystyy kirjoittamaan ohjeiden mukaisen ja teoriakirjallisuutta hyvin hyödyntävän raportin. Opiskelija osoittaa kielenhuollon tuntemusta. Opiskelija pitää suullisen esityksen ohjeiden mukaisesti. Opiskelija asennoituu viestintään positiivisesti sekä osallistuu lähitapaamisten työskentelyyn ja keskusteluun aktiivisesti.

Assessment criteria, excellent (5)

Opiskelija tietää ja ymmärtää, mikä on viestinnän merkitys työyhteisössä ja innostuu pohtimaan viestintää käytännössä esimerkiksi omassa työskentelyssään. Hän pystyy suunnittelemaan ja kirjoittamaan ohjeiden mukaisen ja erinomaisella tavalla teoriakirjallisuutta hyödyntävän raportin. Opiskelija osaa arvioida kielenhuollon osaamistaan ja käyttää tietoperustaa tekstinsä tarkistamisessa. Opiskelija pitää suullisen esityksen ohjeiden mukaisesti ja osaa soveltaa ohjeita ja kokemuksiaan esitykseensä. Opiskelija asennoituu viestintään erittäin positiivisesti sekä osallistuu lähitapaamisten työskentelyyn ja keskusteluun motivoituneena ja tavoitteellisesti.

Qualifications

Participation in the course requires a language proficiency level of C in Finnish.

Objective

In the studies of the Finnish language and communication, you will become familiar with expert and workplace communication. During this course, you will practice communication and interaction skills required in the professional world.

After completing the course, you will be able to:
• operate in communication and interaction situations in your own field
• develop your own communication skills
• consider the recipient, the situation, and the practices of your professional field.

Content

Course content:
- Characteristics of professional communication style
- Analysis and writing of field-specific texts
- Workplace oral communication situations
- Self-assessment of communication skills
- Giving and receiving feedback

Materials

Verkkomateriaali ja opettajan materiaali, jotka jaetaan ItsLearningin kautta.
Mahdollisesti Kauppinen, A.; Nummi, J. & Savola, T. (2012 tai uud.). Tekniikan viestintä. Kirjoittamisen ja puhumisen käsikirja. Helsinki: Edita.

Teaching methods

kontaktiopetus laboratoriotyyppisesti, tehtäväperustaisuus, itsenäinen opiskelu, tiimityö
Suuri osa tehtävistä on mahdollista tehdä vain osallistumalla kontaktiopetukseen, joten läsnäolo tunneilla on tärkeää.

Exam schedules

Opintojaksolla ei ole tenttiä, vaan arviointi perustuu osatehtäviin ja jatkuvaan arviointiin.

International connections

Opintojaksolla opiskellaan laboratoriomaisesti viestinnän ja vuorovaikutuksen perustaitoja, jotka harjaannuttavat oman alan työtehtävissä tarvittaviin vuorovaikutus- ja viestintätaitoihin. Opiskelija tutustuu ennen kontaktitunteja kontaktitunnin aiheisiin, joihin on annettu materiaaleja ja linkkejä Itslearningissa. Opintojaksolla tehtäviä ryhmäharjoituksia tehdään erikokoisissa ja vaihtuvissa pienryhmissä, joissa asiaosaamisen lisäksi harjoitellaan mm. vuorovaikutustaitoja, keskustelu- ja esiintymistaitoja, yhteiskirjoittamisen taitoja, vertaispalautteen antamista suullisesti ja kirjallisesti. Yksilötehtävissä kehitetään yksilöllisiä viestintävalmiuksia. Opintojaksolla käytetään monipuolisesti digitaalista opiskelumateriaalia ja sähköistä oppimisympäristöä videoiden ja tekstien palauttamiseen sekä materiaalin jakamiseen.

Completion alternatives

Ei ole vaillinaista suoritustapaa.

Student workload

Opiskelijan työmäärä koostuu kontaktitunneista (n. 36 t), kotitehtävistä ja itsenäisestä opiskelusta, ennakkotehtävistä, itsenäisestä materiaaliin tutustumisesta ym. (n. 34 t), asiatyylisen tekstin laatimisesta (n. 20 t), puhe-esitykseen valmistautumisesta (n. 20 t) ja kielenhuollon testiin valmistautumisesta (n. 20 t).

Content scheduling

syys–joulukuu 2024
asiantuntija viestijänä, puhe-esityksen valmistautuminen, puhe-esityksiä, asiatyylinen kirjoittaminen ja harjoituksia

Opintojakson tavoitteet, tehtävät ja niiden arviointi, aikataulutus yms. käytännön asiat käydään läpi ensimmäisellä tapaamiskerralla, jolloin opiskelijan on syytä olla paikalla. Ellei opiskelija ole ensimmäisellä kerralla paikalla, on hänen selvitettävä itse opintojakson ensimmäisellä tunnilla käydyt asiat Itslearningin materiaaleista ja Pepistä.

Further information

Participating in the study course is required to have Finnish language skills from the mother tongue level, i.e. C skill level. It is the student's responsibility to check that the prerequisite conditions are met before registering. The teacher has grounds to reject the registration if the prerequisites are not met.

Opintojaksolle osallistuvalta edellytetään äidinkielen tasoista suomen kielen taitoa eli C-taitotasoa. Opiskelijalla on vastuu tarkistaa edeltävyysehtojen täyttyminen ennen ilmoittautumista. Opettajalla on peruste hylätä ilmoittautuminen, jos edeltävyysehdot eivät täyty.

Viestintäkanavana käytetään sähköpostia ja Itslearningia.

Evaluation scale

H-5

Assessment methods and criteria

Arviointi perustuu osatehtäviin ja jatkuvaan arviointiin.
Arvosana muodostuu seuraavasti:
asiatyylinen teksti 25 %
kielenhuollon testi 25 %
suullinen esitys 25 %
tunti- ja kotitehtävät 25 %

Kuhunkin tehtävään liittyvät arviointikriteerit kerrotaan tarkemmin tehtävänannon yhteydessä. Tehtävien palautusajat ovat ehdottomia, myöhästyneitä tehtäviä ei oteta vastaan.
Opiskelijan ilmoittautuminen opintojaksolle poistetaan viimeistään kuukauden kuluttua, ellei ole näyttöä aikomuksesta suorittaa opintojakso.

Assessment criteria, fail (0)

The Finnish language skills of the student participating in the course do not meet the C skill level requirements.

Opiskelija on osallistunut ryhmän työskentelyyn vain vähän tai ei ollenkaan ja/tai ns. tunti-/kotitehtävistä saatu pistemäärä on kokonaisarvioinnissa alle 1 p.

Opiskelija ei ole suorittanut oppimistehtäviä hyväksytysti tai saavuttanut hyväksyttyyn arvosanaan oikeuttavaa pistemäärää oppimistehtävistä..

Opiskelijan ilmoittautuminen opintojaksolle poistetaan viimeistään kuukauden kuluttua, jos hänellä ei ole näyttöä aikomuksesta suorittaa opintojakso.

Assessment criteria, satisfactory (1-2)

Opiskelija pystyy kirjoittamaan asiatyylisen, ohjeiden mukaisen lähdemateriaaliin pohjautuvan raportin. Opiskelija tunnistaa kielenhuollon merkityksen asiatekstissä. Opiskelija pystyy pitämään suullisen esityksen. Hän osallistuu lähitapaamisiin ja keskusteluun osittain.

Assessment criteria, good (3-4)

Opiskelija tietää, mikä on viestinnän merkitys työyhteisössä. Hän pystyy kirjoittamaan ohjeiden mukaisen ja teoriakirjallisuutta hyvin hyödyntävän raportin. Opiskelija osoittaa kielenhuollon tuntemusta. Opiskelija pitää suullisen esityksen ohjeiden mukaisesti. Opiskelija asennoituu viestintään positiivisesti sekä osallistuu lähitapaamisten työskentelyyn ja keskusteluun aktiivisesti.

Assessment criteria, excellent (5)

Opiskelija tietää ja ymmärtää, mikä on viestinnän merkitys työyhteisössä ja innostuu pohtimaan viestintää käytännössä esimerkiksi omassa työskentelyssään. Hän pystyy suunnittelemaan ja kirjoittamaan ohjeiden mukaisen ja erinomaisella tavalla teoriakirjallisuutta hyödyntävän raportin. Opiskelija osaa arvioida kielenhuollon osaamistaan ja käyttää tietoperustaa tekstinsä tarkistamisessa. Opiskelija pitää suullisen esityksen ohjeiden mukaisesti ja osaa soveltaa ohjeita ja kokemuksiaan esitykseensä. Opiskelija asennoituu viestintään erittäin positiivisesti sekä osallistuu lähitapaamisten työskentelyyn ja keskusteluun motivoituneena ja tavoitteellisesti.

Qualifications

Participation in the course requires a language proficiency level of C in Finnish.

Objective

In the studies of the Finnish language and communication, you will become familiar with expert and workplace communication. During this course, you will practice communication and interaction skills required in the professional world.

After completing the course, you will be able to:
• operate in communication and interaction situations in your own field
• develop your own communication skills
• consider the recipient, the situation, and the practices of your professional field.

Content

Course content:
- Characteristics of professional communication style
- Analysis and writing of field-specific texts
- Workplace oral communication situations
- Self-assessment of communication skills
- Giving and receiving feedback

Materials

Verkkomateriaali ja opettajan materiaali, jotka jaetaan ItsLearningin kautta.
Mahdollisesti Kauppinen, A.; Nummi, J. & Savola, T. (2012 tai uud.). Tekniikan viestintä. Kirjoittamisen ja puhumisen käsikirja. Helsinki: Edita.

Teaching methods

kontaktiopetus laboratoriotyyppisesti, tehtäväperustaisuus, itsenäinen opiskelu, tiimityö
Suuri osa tehtävistä on mahdollista tehdä vain osallistumalla kontaktiopetukseen, joten läsnäolo tunneilla on tärkeää.

Exam schedules

Opintojaksolla ei ole tenttiä, vaan arviointi perustuu osatehtäviin ja jatkuvaan arviointiin.

International connections

Opintojaksolla opiskellaan laboratoriomaisesti viestinnän ja vuorovaikutuksen perustaitoja, jotka harjaannuttavat oman alan työtehtävissä tarvittaviin vuorovaikutus- ja viestintätaitoihin. Opiskelija tutustuu ennen kontaktitunteja kontaktitunnin aiheisiin, joihin on annettu materiaaleja ja linkkejä Itslearningissa. Opintojaksolla tehtäviä ryhmäharjoituksia tehdään erikokoisissa ja vaihtuvissa pienryhmissä, joissa asiaosaamisen lisäksi harjoitellaan mm. vuorovaikutustaitoja, keskustelu- ja esiintymistaitoja, yhteiskirjoittamisen taitoja, vertaispalautteen antamista suullisesti ja kirjallisesti. Yksilötehtävissä kehitetään yksilöllisiä viestintävalmiuksia. Opintojaksolla käytetään monipuolisesti digitaalista opiskelumateriaalia ja sähköistä oppimisympäristöä videoiden ja tekstien palauttamiseen sekä materiaalin jakamiseen.

Completion alternatives

Ei ole vaillinaista suoritustapaa.

Student workload

Opiskelijan työmäärä koostuu kontaktitunneista (n. 36 t), kotitehtävistä ja itsenäisestä opiskelusta, ennakkotehtävistä, itsenäisestä materiaaliin tutustumisesta ym. (n. 34 t), asiatyylisen tekstin laatimisesta (n. 20 t), puhe-esitykseen valmistautumisesta (n. 20 t) ja kielenhuollon testiin valmistautumisesta (n. 20 t).

Content scheduling

syys–joulukuu 2024
asiantuntija viestijänä, puhe-esityksen valmistautuminen, puhe-esityksiä, asiatyylinen kirjoittaminen ja harjoituksia

Opintojakson tavoitteet, tehtävät ja niiden arviointi, aikataulutus yms. käytännön asiat käydään läpi ensimmäisellä tapaamiskerralla, jolloin opiskelijan on syytä olla paikalla. Ellei opiskelija ole ensimmäisellä kerralla paikalla, on hänen selvitettävä itse opintojakson ensimmäisellä tunnilla käydyt asiat Itslearningin materiaaleista ja Pepistä.

Further information

Participating in the study course is required to have Finnish language skills from the mother tongue level, i.e. C skill level. It is the student's responsibility to check that the prerequisite conditions are met before registering. The teacher has grounds to reject the registration if the prerequisites are not met.

Opintojaksolle osallistuvalta edellytetään äidinkielen tasoista suomen kielen taitoa eli C-taitotasoa. Opiskelijalla on vastuu tarkistaa edeltävyysehtojen täyttyminen ennen ilmoittautumista. Opettajalla on peruste hylätä ilmoittautuminen, jos edeltävyysehdot eivät täyty.

Viestintäkanavana käytetään sähköpostia ja Itslearningia.

Evaluation scale

H-5

Assessment methods and criteria

Arviointi perustuu osatehtäviin ja jatkuvaan arviointiin.
Arvosana muodostuu seuraavasti:
asiatyylinen teksti 25 %
kielenhuollon testi 25 %
suullinen esitys 25 %
tunti- ja kotitehtävät 25 %

Kuhunkin tehtävään liittyvät arviointikriteerit kerrotaan tarkemmin tehtävänannon yhteydessä. Tehtävien palautusajat ovat ehdottomia, myöhästyneitä tehtäviä ei oteta vastaan.
Opiskelijan ilmoittautuminen opintojaksolle poistetaan viimeistään kuukauden kuluttua, ellei ole näyttöä aikomuksesta suorittaa opintojakso.

Assessment criteria, fail (0)

The Finnish language skills of the student participating in the course do not meet the C skill level requirements.

Opiskelija on osallistunut ryhmän työskentelyyn vain vähän tai ei ollenkaan ja/tai ns. tunti-/kotitehtävistä saatu pistemäärä on kokonaisarvioinnissa alle 1 p.

Opiskelija ei ole suorittanut oppimistehtäviä hyväksytysti tai saavuttanut hyväksyttyyn arvosanaan oikeuttavaa pistemäärää oppimistehtävistä..

Opiskelijan ilmoittautuminen opintojaksolle poistetaan viimeistään kuukauden kuluttua, jos hänellä ei ole näyttöä aikomuksesta suorittaa opintojakso.

Assessment criteria, satisfactory (1-2)

Opiskelija pystyy kirjoittamaan asiatyylisen, ohjeiden mukaisen lähdemateriaaliin pohjautuvan raportin. Opiskelija tunnistaa kielenhuollon merkityksen asiatekstissä. Opiskelija pystyy pitämään suullisen esityksen. Hän osallistuu lähitapaamisiin ja keskusteluun osittain.

Assessment criteria, good (3-4)

Opiskelija tietää, mikä on viestinnän merkitys työyhteisössä. Hän pystyy kirjoittamaan ohjeiden mukaisen ja teoriakirjallisuutta hyvin hyödyntävän raportin. Opiskelija osoittaa kielenhuollon tuntemusta. Opiskelija pitää suullisen esityksen ohjeiden mukaisesti. Opiskelija asennoituu viestintään positiivisesti sekä osallistuu lähitapaamisten työskentelyyn ja keskusteluun aktiivisesti.

Assessment criteria, excellent (5)

Opiskelija tietää ja ymmärtää, mikä on viestinnän merkitys työyhteisössä ja innostuu pohtimaan viestintää käytännössä esimerkiksi omassa työskentelyssään. Hän pystyy suunnittelemaan ja kirjoittamaan ohjeiden mukaisen ja erinomaisella tavalla teoriakirjallisuutta hyödyntävän raportin. Opiskelija osaa arvioida kielenhuollon osaamistaan ja käyttää tietoperustaa tekstinsä tarkistamisessa. Opiskelija pitää suullisen esityksen ohjeiden mukaisesti ja osaa soveltaa ohjeita ja kokemuksiaan esitykseensä. Opiskelija asennoituu viestintään erittäin positiivisesti sekä osallistuu lähitapaamisten työskentelyyn ja keskusteluun motivoituneena ja tavoitteellisesti.

Qualifications

Participation in the course requires a language proficiency level of C in Finnish.

Objective

In the studies of the Finnish language and communication, you will become familiar with expert and workplace communication. During this course, you will practice communication and interaction skills required in the professional world.

After completing the course, you will be able to:
• operate in communication and interaction situations in your own field
• develop your own communication skills
• consider the recipient, the situation, and the practices of your professional field.

Content

Course content:
- Characteristics of professional communication style
- Analysis and writing of field-specific texts
- Workplace oral communication situations
- Self-assessment of communication skills
- Giving and receiving feedback

Materials

Verkkomateriaali ja opettajan materiaali, jotka jaetaan ItsLearningin kautta.

Teaching methods

kontaktiopetus laboratoriotyyppisesti, tehtäväperustaisuus, itsenäinen opiskelu, tiimityö
Suuri osa tehtävistä on mahdollista tehdä vain osallistumalla kontaktiopetukseen, joten läsnäolo tunneilla on tärkeää.

Exam schedules

Opintojaksolla ei ole tenttiä, vaan arviointi perustuu osatehtäviin ja jatkuvaan arviointiin.

International connections

Opintojaksolla opiskellaan laboratoriomaisesti viestinnän ja vuorovaikutuksen perustaitoja, jotka harjaannuttavat oman alan työtehtävissä tarvittaviin vuorovaikutus- ja viestintätaitoihin. Opiskelija tutustuu ennen kontaktitunteja kontaktitunnin aiheisiin, joihin on annettu materiaaleja ja linkkejä Itslearningissa. Opintojaksolla tehtäviä ryhmäharjoituksia tehdään erikokoisissa ja vaihtuvissa pienryhmissä, joissa asiaosaamisen lisäksi harjoitellaan mm. vuorovaikutustaitoja, keskustelu- ja esiintymistaitoja, yhteiskirjoittamisen taitoja, vertaispalautteen antamista suullisesti ja kirjallisesti. Yksilötehtävissä kehitetään yksilöllisiä viestintävalmiuksia. Opintojaksolla käytetään monipuolisesti digitaalista opiskelumateriaalia ja sähköistä oppimisympäristöä videoiden ja tekstien palauttamiseen sekä materiaalin jakamiseen.

Completion alternatives

Ei ole vaillinaista suoritustapaa.

Student workload

Opiskelijan työmäärä koostuu kontaktitunneista (n. 36 t), kotitehtävistä ja itsenäisestä opiskelusta, ennakkotehtävistä, itsenäisestä materiaaliin tutustumisesta ym. (n. 34 t), asiatyylisen tekstin laatimisesta (n. 20 t), puhe-esitykseen valmistautumisesta (n. 20 t) ja kielenhuollon testiin valmistautumisesta (n. 20 t).

Content scheduling

tammi–huhtikuu 2025
asiantuntija viestijänä, puhe-esityksen valmistautuminen, puhe-esityksiä, asiatyylinen kirjoittaminen ja harjoituksia

Opintojakson tavoitteet, tehtävät ja niiden arviointi, aikataulutus yms. käytännön asiat käydään läpi ensimmäisellä tapaamiskerralla, jolloin opiskelijan on syytä olla paikalla. Ellei opiskelija ole ensimmäisellä kerralla paikalla, on hänen selvitettävä itse opintojakson ensimmäisellä tunnilla käydyt asiat Itslearningin materiaaleista ja Pepistä.

Further information

Participating in the study course is required to have Finnish language skills from the mother tongue level, i.e. C skill level. It is the student's responsibility to check that the prerequisite conditions are met before registering. The teacher has grounds to reject the registration if the prerequisites are not met.

Opintojaksolle osallistuvalta edellytetään äidinkielen tasoista suomen kielen taitoa eli C-taitotasoa. Opiskelijalla on vastuu tarkistaa edeltävyysehtojen täyttyminen ennen ilmoittautumista. Opettajalla on peruste hylätä ilmoittautuminen, jos edeltävyysehdot eivät täyty.

Viestintäkanavana käytetään sähköpostia ja Itslearningia.

Evaluation scale

H-5

Assessment methods and criteria

Arviointi perustuu osatehtäviin ja jatkuvaan arviointiin.
Arvosana muodostuu seuraavasti:
asiatyylinen teksti 25 %
kielenhuollon testi 25 %
suullinen esitys 25 %
tunti- ja kotitehtävät 25 %

Kuhunkin tehtävään liittyvät arviointikriteerit kerrotaan tarkemmin tehtävänannon yhteydessä. Tehtävien palautusajat ovat ehdottomia, myöhästyneitä tehtäviä ei oteta vastaan.
Opiskelijan ilmoittautuminen opintojaksolle poistetaan viimeistään kuukauden kuluttua, ellei ole näyttöä aikomuksesta suorittaa opintojakso.

Assessment criteria, fail (0)

The Finnish language skills of the student participating in the course do not meet the C skill level requirements.

Opiskelija on osallistunut ryhmän työskentelyyn vain vähän tai ei ollenkaan ja/tai ns. tunti-/kotitehtävistä saatu pistemäärä on kokonaisarvioinnissa alle 1 p.

Opiskelija ei ole suorittanut oppimistehtäviä hyväksytysti tai saavuttanut hyväksyttyyn arvosanaan oikeuttavaa pistemäärää oppimistehtävistä..

Opiskelijan ilmoittautuminen opintojaksolle poistetaan viimeistään kuukauden kuluttua, jos hänellä ei ole näyttöä aikomuksesta suorittaa opintojakso.

Assessment criteria, satisfactory (1-2)

Opiskelija pystyy kirjoittamaan asiatyylisen, ohjeiden mukaisen lähdemateriaaliin pohjautuvan raportin. Opiskelija tunnistaa kielenhuollon merkityksen asiatekstissä. Opiskelija pystyy pitämään suullisen esityksen. Hän osallistuu lähitapaamisiin ja keskusteluun osittain.

Assessment criteria, good (3-4)

Opiskelija tietää, mikä on viestinnän merkitys työyhteisössä. Hän pystyy kirjoittamaan ohjeiden mukaisen ja teoriakirjallisuutta hyvin hyödyntävän raportin. Opiskelija osoittaa kielenhuollon tuntemusta. Opiskelija pitää suullisen esityksen ohjeiden mukaisesti. Opiskelija asennoituu viestintään positiivisesti sekä osallistuu lähitapaamisten työskentelyyn ja keskusteluun aktiivisesti.

Assessment criteria, excellent (5)

Opiskelija tietää ja ymmärtää, mikä on viestinnän merkitys työyhteisössä ja innostuu pohtimaan viestintää käytännössä esimerkiksi omassa työskentelyssään. Hän pystyy suunnittelemaan ja kirjoittamaan ohjeiden mukaisen ja erinomaisella tavalla teoriakirjallisuutta hyödyntävän raportin. Opiskelija osaa arvioida kielenhuollon osaamistaan ja käyttää tietoperustaa tekstinsä tarkistamisessa. Opiskelija pitää suullisen esityksen ohjeiden mukaisesti ja osaa soveltaa ohjeita ja kokemuksiaan esitykseensä. Opiskelija asennoituu viestintään erittäin positiivisesti sekä osallistuu lähitapaamisten työskentelyyn ja keskusteluun motivoituneena ja tavoitteellisesti.

Qualifications

Participation in the course requires a language proficiency level of C in Finnish.

Objective

In the studies of the Finnish language and communication, you will become familiar with expert and workplace communication. During this course, you will practice communication and interaction skills required in the professional world.

After completing the course, you will be able to:
• operate in communication and interaction situations in your own field
• develop your own communication skills
• consider the recipient, the situation, and the practices of your professional field.

Content

Course content:
- Characteristics of professional communication style
- Analysis and writing of field-specific texts
- Workplace oral communication situations
- Self-assessment of communication skills
- Giving and receiving feedback

Materials

Verkkomateriaali ja opettajan materiaali, jotka jaetaan ItsLearningin kautta.

Teaching methods

kontaktiopetus laboratoriotyyppisesti, tehtäväperustaisuus, itsenäinen opiskelu, tiimityö
Suuri osa tehtävistä on mahdollista tehdä vain osallistumalla kontaktiopetukseen, joten läsnäolo tunneilla on tärkeää.

Exam schedules

Opintojaksolla ei ole tenttiä, vaan arviointi perustuu osatehtäviin ja jatkuvaan arviointiin.

International connections

Opintojaksolla opiskellaan laboratoriomaisesti viestinnän ja vuorovaikutuksen perustaitoja, jotka harjaannuttavat oman alan työtehtävissä tarvittaviin vuorovaikutus- ja viestintätaitoihin. Opiskelija tutustuu ennen kontaktitunteja kontaktitunnin aiheisiin, joihin on annettu materiaaleja ja linkkejä Itslearningissa. Opintojaksolla tehtäviä ryhmäharjoituksia tehdään erikokoisissa ja vaihtuvissa pienryhmissä, joissa asiaosaamisen lisäksi harjoitellaan mm. vuorovaikutustaitoja, keskustelu- ja esiintymistaitoja, yhteiskirjoittamisen taitoja, vertaispalautteen antamista suullisesti ja kirjallisesti. Yksilötehtävissä kehitetään yksilöllisiä viestintävalmiuksia. Opintojaksolla käytetään monipuolisesti digitaalista opiskelumateriaalia ja sähköistä oppimisympäristöä videoiden ja tekstien palauttamiseen sekä materiaalin jakamiseen.

Completion alternatives

Ei ole vaillinaista suoritustapaa.

Student workload

Opiskelijan työmäärä koostuu kontaktitunneista (n. 36 t), kotitehtävistä ja itsenäisestä opiskelusta, ennakkotehtävistä, itsenäisestä materiaaliin tutustumisesta ym. (n. 34 t), asiatyylisen tekstin laatimisesta (n. 20 t), puhe-esitykseen valmistautumisesta (n. 20 t) ja kielenhuollon testiin valmistautumisesta (n. 20 t).

Content scheduling

tammi–huhtikuu 2025
asiantuntija viestijänä, puhe-esityksen valmistautuminen, puhe-esityksiä, asiatyylinen kirjoittaminen ja harjoituksia

Opintojakson tavoitteet, tehtävät ja niiden arviointi, aikataulutus yms. käytännön asiat käydään läpi ensimmäisellä tapaamiskerralla, jolloin opiskelijan on syytä olla paikalla. Ellei opiskelija ole ensimmäisellä kerralla paikalla, on hänen selvitettävä itse opintojakson ensimmäisellä tunnilla käydyt asiat Itslearningin materiaaleista ja Pepistä.

Further information

Participating in the study course is required to have Finnish language skills from the mother tongue level, i.e. C skill level. It is the student's responsibility to check that the prerequisite conditions are met before registering. The teacher has grounds to reject the registration if the prerequisites are not met.

Opintojaksolle osallistuvalta edellytetään äidinkielen tasoista suomen kielen taitoa eli C-taitotasoa. Opiskelijalla on vastuu tarkistaa edeltävyysehtojen täyttyminen ennen ilmoittautumista. Opettajalla on peruste hylätä ilmoittautuminen, jos edeltävyysehdot eivät täyty.

Viestintäkanavana käytetään sähköpostia ja Itslearningia.

Evaluation scale

H-5

Assessment methods and criteria

Arviointi perustuu osatehtäviin ja jatkuvaan arviointiin.
Arvosana muodostuu seuraavasti:
asiatyylinen teksti 25 %
kielenhuollon testi 25 %
suullinen esitys 25 %
tunti- ja kotitehtävät 25 %

Kuhunkin tehtävään liittyvät arviointikriteerit kerrotaan tarkemmin tehtävänannon yhteydessä. Tehtävien palautusajat ovat ehdottomia, myöhästyneitä tehtäviä ei oteta vastaan.
Opiskelijan ilmoittautuminen opintojaksolle poistetaan viimeistään kuukauden kuluttua, ellei ole näyttöä aikomuksesta suorittaa opintojakso.

Assessment criteria, fail (0)

The Finnish language skills of the student participating in the course do not meet the C skill level requirements.

Opiskelija on osallistunut ryhmän työskentelyyn vain vähän tai ei ollenkaan ja/tai ns. tunti-/kotitehtävistä saatu pistemäärä on kokonaisarvioinnissa alle 1 p.

Opiskelija ei ole suorittanut oppimistehtäviä hyväksytysti tai saavuttanut hyväksyttyyn arvosanaan oikeuttavaa pistemäärää oppimistehtävistä..

Opiskelijan ilmoittautuminen opintojaksolle poistetaan viimeistään kuukauden kuluttua, jos hänellä ei ole näyttöä aikomuksesta suorittaa opintojakso.

Assessment criteria, satisfactory (1-2)

Opiskelija pystyy kirjoittamaan asiatyylisen, ohjeiden mukaisen lähdemateriaaliin pohjautuvan raportin. Opiskelija tunnistaa kielenhuollon merkityksen asiatekstissä. Opiskelija pystyy pitämään suullisen esityksen. Hän osallistuu lähitapaamisiin ja keskusteluun osittain.

Assessment criteria, good (3-4)

Opiskelija tietää, mikä on viestinnän merkitys työyhteisössä. Hän pystyy kirjoittamaan ohjeiden mukaisen ja teoriakirjallisuutta hyvin hyödyntävän raportin. Opiskelija osoittaa kielenhuollon tuntemusta. Opiskelija pitää suullisen esityksen ohjeiden mukaisesti. Opiskelija asennoituu viestintään positiivisesti sekä osallistuu lähitapaamisten työskentelyyn ja keskusteluun aktiivisesti.

Assessment criteria, excellent (5)

Opiskelija tietää ja ymmärtää, mikä on viestinnän merkitys työyhteisössä ja innostuu pohtimaan viestintää käytännössä esimerkiksi omassa työskentelyssään. Hän pystyy suunnittelemaan ja kirjoittamaan ohjeiden mukaisen ja erinomaisella tavalla teoriakirjallisuutta hyödyntävän raportin. Opiskelija osaa arvioida kielenhuollon osaamistaan ja käyttää tietoperustaa tekstinsä tarkistamisessa. Opiskelija pitää suullisen esityksen ohjeiden mukaisesti ja osaa soveltaa ohjeita ja kokemuksiaan esitykseensä. Opiskelija asennoituu viestintään erittäin positiivisesti sekä osallistuu lähitapaamisten työskentelyyn ja keskusteluun motivoituneena ja tavoitteellisesti.

Qualifications

Participation in the course requires a language proficiency level of C in Finnish.

Objective

In the studies of the Finnish language and communication, you will become familiar with expert and workplace communication. During this course, you will practice communication and interaction skills required in the professional world.

After completing the course, you will be able to:
• operate in communication and interaction situations in your own field
• develop your own communication skills
• consider the recipient, the situation, and the practices of your professional field.

Content

Course content:
- Characteristics of professional communication style
- Analysis and writing of field-specific texts
- Workplace oral communication situations
- Self-assessment of communication skills
- Giving and receiving feedback

Materials

Verkkomateriaali ja opettajan materiaali, jotka jaetaan ItsLearningin kautta.

Teaching methods

kontaktiopetus laboratoriotyyppisesti, tehtäväperustaisuus, itsenäinen opiskelu, tiimityö
Suuri osa tehtävistä on mahdollista tehdä vain osallistumalla kontaktiopetukseen, joten läsnäolo tunneilla on tärkeää.

Exam schedules

Opintojaksolla ei ole tenttiä, vaan arviointi perustuu osatehtäviin ja jatkuvaan arviointiin.

International connections

Opintojaksolla opiskellaan laboratoriomaisesti viestinnän ja vuorovaikutuksen perustaitoja, jotka harjaannuttavat oman alan työtehtävissä tarvittaviin vuorovaikutus- ja viestintätaitoihin. Opiskelija tutustuu ennen kontaktitunteja kontaktitunnin aiheisiin, joihin on annettu materiaaleja ja linkkejä Itslearningissa. Opintojaksolla tehtäviä ryhmäharjoituksia tehdään erikokoisissa ja vaihtuvissa pienryhmissä, joissa asiaosaamisen lisäksi harjoitellaan mm. vuorovaikutustaitoja, keskustelu- ja esiintymistaitoja, yhteiskirjoittamisen taitoja, vertaispalautteen antamista suullisesti ja kirjallisesti. Yksilötehtävissä kehitetään yksilöllisiä viestintävalmiuksia. Opintojaksolla käytetään monipuolisesti digitaalista opiskelumateriaalia ja sähköistä oppimisympäristöä videoiden ja tekstien palauttamiseen sekä materiaalin jakamiseen.

Completion alternatives

Ei ole vaillinaista suoritustapaa.

Student workload

Opiskelijan työmäärä koostuu kontaktitunneista (n. 36 t), kotitehtävistä ja itsenäisestä opiskelusta, ennakkotehtävistä, itsenäisestä materiaaliin tutustumisesta ym. (n. 34 t), asiatyylisen tekstin laatimisesta (n. 20 t), puhe-esitykseen valmistautumisesta (n. 20 t) ja kielenhuollon testiin valmistautumisesta (n. 20 t).

Content scheduling

tammi–huhtikuu 2025
asiantuntija viestijänä, puhe-esityksen valmistautuminen, puhe-esityksiä, asiatyylinen kirjoittaminen ja harjoituksia

Opintojakson tavoitteet, tehtävät ja niiden arviointi, aikataulutus yms. käytännön asiat käydään läpi ensimmäisellä tapaamiskerralla, jolloin opiskelijan on syytä olla paikalla. Ellei opiskelija ole ensimmäisellä kerralla paikalla, on hänen selvitettävä itse opintojakson ensimmäisellä tunnilla käydyt asiat Itslearningin materiaaleista ja Pepistä.

Further information

Participating in the study course is required to have Finnish language skills from the mother tongue level, i.e. C skill level. It is the student's responsibility to check that the prerequisite conditions are met before registering. The teacher has grounds to reject the registration if the prerequisites are not met.

Opintojaksolle osallistuvalta edellytetään äidinkielen tasoista suomen kielen taitoa eli C-taitotasoa. Opiskelijalla on vastuu tarkistaa edeltävyysehtojen täyttyminen ennen ilmoittautumista. Opettajalla on peruste hylätä ilmoittautuminen, jos edeltävyysehdot eivät täyty.

Viestintäkanavana käytetään sähköpostia ja Itslearningia.

Evaluation scale

H-5

Assessment methods and criteria

Arviointi perustuu osatehtäviin ja jatkuvaan arviointiin.
Arvosana muodostuu seuraavasti:
asiatyylinen teksti 25 %
kielenhuollon testi 25 %
suullinen esitys 25 %
tunti- ja kotitehtävät 25 %

Kuhunkin tehtävään liittyvät arviointikriteerit kerrotaan tarkemmin tehtävänannon yhteydessä. Tehtävien palautusajat ovat ehdottomia, myöhästyneitä tehtäviä ei oteta vastaan.
Opiskelijan ilmoittautuminen opintojaksolle poistetaan viimeistään kuukauden kuluttua, ellei ole näyttöä aikomuksesta suorittaa opintojakso.

Assessment criteria, fail (0)

The Finnish language skills of the student participating in the course do not meet the C skill level requirements.

Opiskelija on osallistunut ryhmän työskentelyyn vain vähän tai ei ollenkaan ja/tai ns. tunti-/kotitehtävistä saatu pistemäärä on kokonaisarvioinnissa alle 1 p.

Opiskelija ei ole suorittanut oppimistehtäviä hyväksytysti tai saavuttanut hyväksyttyyn arvosanaan oikeuttavaa pistemäärää oppimistehtävistä..

Opiskelijan ilmoittautuminen opintojaksolle poistetaan viimeistään kuukauden kuluttua, jos hänellä ei ole näyttöä aikomuksesta suorittaa opintojakso.

Assessment criteria, satisfactory (1-2)

Opiskelija pystyy kirjoittamaan asiatyylisen, ohjeiden mukaisen lähdemateriaaliin pohjautuvan raportin. Opiskelija tunnistaa kielenhuollon merkityksen asiatekstissä. Opiskelija pystyy pitämään suullisen esityksen. Hän osallistuu lähitapaamisiin ja keskusteluun osittain.

Assessment criteria, good (3-4)

Opiskelija tietää, mikä on viestinnän merkitys työyhteisössä. Hän pystyy kirjoittamaan ohjeiden mukaisen ja teoriakirjallisuutta hyvin hyödyntävän raportin. Opiskelija osoittaa kielenhuollon tuntemusta. Opiskelija pitää suullisen esityksen ohjeiden mukaisesti. Opiskelija asennoituu viestintään positiivisesti sekä osallistuu lähitapaamisten työskentelyyn ja keskusteluun aktiivisesti.

Assessment criteria, excellent (5)

Opiskelija tietää ja ymmärtää, mikä on viestinnän merkitys työyhteisössä ja innostuu pohtimaan viestintää käytännössä esimerkiksi omassa työskentelyssään. Hän pystyy suunnittelemaan ja kirjoittamaan ohjeiden mukaisen ja erinomaisella tavalla teoriakirjallisuutta hyödyntävän raportin. Opiskelija osaa arvioida kielenhuollon osaamistaan ja käyttää tietoperustaa tekstinsä tarkistamisessa. Opiskelija pitää suullisen esityksen ohjeiden mukaisesti ja osaa soveltaa ohjeita ja kokemuksiaan esitykseensä. Opiskelija asennoituu viestintään erittäin positiivisesti sekä osallistuu lähitapaamisten työskentelyyn ja keskusteluun motivoituneena ja tavoitteellisesti.

Qualifications

Participation in the course requires a language proficiency level of C in Finnish.