Study Guide

Materials

Materials used in the course:

1. ISO27005 standardi
2. Sutton, David (2021): Information security risk management : a practitioner's guide: https://ebookcentral.proquest.com/lib/turkuamk-ebooks/detail.action?docID=6733537
3. Ilmonen, I. & al. (2022): Johda riskejä: käytännön opas yrityksen riskienhallintaan: https://turkuamk.finna.fi/Record/turkuamk.995697291505970?sid=3091696371
4. https://www.enisa.europa.eu/publications/interoperable-eu-risk-management-framework
5. Enisa Threat Landscape 2023 https://www.enisa.europa.eu/publications/enisa-threat-landscape-2023

And potentially other relevant materials

Teaching methods

Theoretical part through lectures and independent study. Guidance through remote meetings as needed. Practical risk assessment work requires acquiring the target company and maintaining communication with the responsible party. On site meetings for guidance, peer support, sharing experiences, project presentations, and evaluations in the upcoming days

International connections

Active project-based learning and problem-solving

Completion alternatives

-

Student workload

Review of the theory section of the information security risk management course and an extensive risk management project

Content scheduling

Information and Cybersecurity are critical areas in modern organizations, and the importance of risk management has been further emphasized. This practical project-based course in risk management provides students with an opportunity to apply the principles and methods of information and cybersecurity risk management in practice. The course aims to develop students' skills in risk identification, assessment, and management, preparing them for future careers in the field of information and cybersecurity.

Course Content:

Prerequisite for this course is a course in information security risk management, covering the ISO 27005 standard risk management process. Students should have a good understanding of the stages of the information and cybersecurity risk management process, including risk identification, assessment, management, and monitoring. The process and stages are reviewed at the beginning of this course.

The student acquires a small or medium-sized organization for which they will conduct a risk assessment. The student is responsible for contacting the organization's representatives. The work can be done individually or in pairs

Students will apply the ISO 27005 standard, along with other risk management frameworks and best practices, to their selected target organization. They will perform the risk assessment and document the results. At the end of the course, students will compile a final report, including the risk assessment findings and recommendations for the target organization. They will present their findings to the class and possibly to representatives from the chosen organization.

Requirements:

Participation in this course requires prior knowledge of information and cybersecurity risk management. Students must also select a target organization for the risk assessment.

This course offers students a unique opportunity to apply their knowledge of risk management to a real-world project and prepares them for careers in the field of information and cybersecurity.

Timeframe:
Spring 2024. Bi-weekly in-person meetings and bi-weekly online meetings based on separate reservations

Evaluation scale

H-5

Assessment methods and criteria

Review task for the theory section 10%
Implementation, documentation, and feedback from the organization for the risk assessment 90%

Assessment criteria, fail (0)

No risk assessment has been conducted

Assessment criteria, satisfactory (1-2)

A brief risk assessment and satisfactory feedback from the organization.

Assessment criteria, good (3-4)

A fairly comprehensive risk assessment and positive feedback from the organization

Assessment criteria, excellent (5)

A comprehensive risk assessment and excellent feedback from the organization

Objective

After completing this course student can:

Install Git Bash
Initialize repository and commit code to Git
Create, use and merge branches
Use stashing and unstashing
Use Git remotes, push and pull code from Git remotes

Content

Basic use of Git locally and Git remotes.

Materials

In Itslearning
Internet

Teaching methods

Self study
Practical assignment

Exam schedules

No exam

International connections

Self study

Completion alternatives

-

Student workload

Practical assignment and self study 27 hours

Assessment criteria, approved/failed

Course is passed, if the assignment is done and returned according to instructions.

Content scheduling

Course is a self-paced non-stop course about the basic use of Git locally and Git remotes (such as GitLab).

After completing this course student can:
Install Git Bash
Initialize repository and commit code to Git repository using Git bash
Create, use and merge branches
Use stashing and unstashing
Use Git remotes, push and pull code from Git remotes

Enroll to course in Peppi. After teachers have accepted your enrollment in Peppi, you should see the course's workspace in Itslearning automatically (within a few days due to delay in the Peppi <> Itslearning integration).

Further information

Itslearning

Enroll to course in Peppi. When your enrollment is accepted, you'll get access to course's Itslearning (within a day or two after enrollment acceptance).

Evaluation scale

Hyväksytty/Hylätty

Assessment methods and criteria

Quality of the returned assignment.

Objective

After completing the course the student can:
- describe basic solutions for data architectures and big data
- select and use suitable data architecture
- apply ETL process and tools for handling of big data

Content

Architecture and Components of Big Data Frameworks
ETL process with Big Data for batch and streaming
Practical work with suitable tools and frameworks

Materials

Teacher provided lecture material
Supporting public online material
Teacher provided virtual machines
All needed material (or at least a link to them) will be available in itslearning.

Teaching methods

Contact learning, practical exercises, independent study

International connections

Given examples and exercises support each topic studied during the lectures. Additional material in the form of tutorials and reliable information sources is provided.

Student workload

Contact hours 56 h
Inpendent studying 79h, including:
- Studying the course material
- Completing exercises
- Project

Content scheduling

-The basic idea of data engineering methods and pipelines
-different components
-integration of said components (MQ systems)
-data engineering frameworks (Apache family)
-The goal of the course is to be able to build a data pipeline from start to finish

Further information

Itslearning and contact classes are the main communication channels used on this course.

The student is required to have a computer capable of running a simple Ubuntu virtual machine.

Evaluation scale

H-5

Assessment methods and criteria

Homework exercises returned throughout the course
Small project at the end of the course

Objective

By the end of the course students will have the knowledge to:
• Create a podcast concept
• Understand how to brand a podcast
• Assess and chooses recording equipment
• Script, record, and edit a podcast
• Understand the different distribution channels and assess their strengths and weaknesses
• Know how to market and promote a podcast
• Understand IPR and know where to access royalty free music

Content

Podcast concept and research
Branding
Scripting
Recording
Audio editing
Distribution
Transcription
Marketing
IPR

Materials

Teacher supplied material as required

Teaching methods

Interactive classroom lectures and group work. Students will work in self-assigned groups drawing from research and their own ideas, opinions and experiences.

Exam schedules

There is no exam for this course

International connections

Students will learn the process of podcast creation from initial concept through to recording and editing a finished 20 minute podcast episode. The course will include:
Developing a podcast concept
Creating a brand - including name and logo
Scripting
Transcription - AI as a help
Distribution channels
Recording - equipment, room requirements
Audio editing
Marketing
IPR

Completion alternatives

None

Student workload

Classroom activities: 30 h
Group work: 20 h

Content scheduling

Podcast concepting and research
Researching podcast themes
Researching audiences
Researching niche opportunities
Researching formats - Interviews, music, discussion, reporting?
Researching how using AI can help with the concept

Further information

This course is for anyone with an interest in starting a podcast. It is practical with a strong emphasis on learning by doing. By the end of the course each group will have a fully defined podcast concept, a clear brand outline, a marketing roadmap and one ready to publish podcast episode in the bag. Although the language of instruction is English your podcast can be recorded in your language of preference.

Evaluation scale

H-5

Assessment methods and criteria

Assessment is a combination of teacher observation of student commitment, effort and engagement during lessons together with the standard of 4 completed classroom task based assignments. Students will be assessed on overall communicative competence and language appropriacy within specific communication contexts

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.

Assessment criteria, satisfactory (1-2)

The student has completed the tasks with the minimum of set requirements stated in the task instructions. The student has completed tasks later than the given deadlines. The student has not addressed feedback provided by the teacher.

Assessment criteria, good (3-4)

The student has completed the tasks well fulfilling most of the set requirements stated 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 reflected on their own performance and has been given peer feedback.

Assessment criteria, excellent (5)

The student has completed the tasks very well fulfilling or surpassing the set requirements as stated in the task instructions. The student has completed tasks within the given deadlines or earlier and has addressed feedback provided by the teacher. The student has been giving quality peer feedback.

Evaluation scale

H-5

Objective

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

Content

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.

Exam schedules

No Exam.

International connections

The course includes approximately 13 guided working and theory sessions, 9 personal practice tasks and a group work final project.
*
Final project is done in groups of 3-4 people outside of guidance sessions. The group sets aside 15 minutes to present the group work during the last session.

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 70 hours

Total: approximately: 135 hours

Content scheduling

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


We proceed in general according to the chapters in the course book.

Further information

Qualifications:

- Python programming skills and skills in utilizing Pandas for data manipulation and Numpy for numerical operations and array handling are required.
- Basic knowledge of probability, statistics and linear algebra is also beneficial.

Evaluation scale

H-5

Assessment methods and criteria

- The course is graded on a scale of 0-5.
- In order to receive an approved performance, the student must receive an acceptable mark for both 1) personal practice tasks (exercises) and 2) teamwork project.
- You get points from the 9 homework exercises, which affect the evaluation by 3 units.
- Occasionally, there may be classwork exercises, but their points are mostly optional and are considered as bonuses.
- The project work also affects the evaluation by 2 units. The project work is graded in ITS from 0 to 5, which is influenced by both the teacher's assessment and the peer assessment given by the rest of the project team.
- The course can only be passed by doing both personal practice tasks and participating in teamwork project.

Assessment criteria, fail (0)

The student does NOT participate in the project work or gets the project work grade 0 (Failed) OR did not get at least 40% 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 60-84% of the points for the exercises in the course AND got a grade of 3 - 4 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 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 sessions when 3 hours for theory and practical exercises.
Additionally, weekly 1h sessions for questions and support in exercises.

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

-

Student workload

Contact hours
- Course introduction: 3 hours
- 12 times 3h theory and practice: 12 x 3h = 36 hours
- 10 times Questions & Support: 10 x 1h = 10 hours

Home work:
- Working with assignments: approximately 80 hours

Total: approximately 130 hours

Content scheduling

Week 2: Course introduction

Weeks 2 - 15
- 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 points from practical exercises in class room and home work exercises.
Around half of the exercises are done during the contact hours.

Additionally, there is an exam during the last contact session that will be used an option to pass the course with grade 1 or 2.

Assessment criteria, fail (0)

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

Assessment criteria, satisfactory (1-2)

50% - 69% points in the exercises OR student has passed the test in the final contact session.

Assessment criteria, good (3-4)

70% - 89% points in the exercises.

Assessment criteria, excellent (5)

At least 90% points in the exercises.

Qualifications

Introduction to Programming, or equivalent programming skills

Objective

After completing the course the student can:
- list regulations of data protection in Finland and in EU
- give examples of the duties of personnel working with data protection and privacy
- construct a privacy policy
- protect his/her privacy in electronic data communication
- provide examples of the rights to check how his/her own privacy has been protected in different environments
- plan and conduct actions required by the data and privacy protection in an SME sector enterprise or similar size organization
- assess the efficiency of these actions and give justified improvement proposals for them

Content

The course contains knowledge of the following areas:
- General Data Protection Regulation
- Practical Data Protection
- Online Privacy

Materials

Oppimateriaali ja tehtävät ovat Itslearningissä.

Exam schedules

Kurssin puolivälissä.

International connections

Luennot, henkilökohtaiset tehtävät, ryhmätyö, tentti.

Student workload

Ryhmätyö käytännön tietosuojakysymyksistä. Pakollinen läsnäolo töiden esittelyissä.
Luennot: 26h
Henkilökohtaiset tehtävät ja ryhmätyö: 80h
Koe (sisältäen valmistautumisen): 29h

Content scheduling

Tietosuojan säännökset Suomessa, EU:ssa ja maailmalla.
Tietosuojavaltuutetun toiminta ja tehtävät.
Tietosuojavastaavan toiminta ja tehtävät.
Tiedon suojaaminen tietoliikenteessä.
Yksityisyyden turvaaminen lainsäädännössä.
Työelämän tietosuoja.
Tiedon suojaaminen sosiaalisessa mediassa ja internetissä.

Further information

Kurssi ja sen viestintä on Itslearningissä.

Evaluation scale

H-5

Assessment methods and criteria

Henkilökohtaiset tehtävät, ryhmätyö, tentti. Jokaisesta osasta on saatava hyväksytty arvosana.

Assessment criteria, fail (0)

Hylätty arvosana henkilökohtaisista tehtävistä, ryhmätyöstä tai tentistä.

Assessment criteria, satisfactory (1-2)

40%-55% henkilökohtaisista tehtävistä palautettu hyväksytysti.
40%-55% hyväksytty suoritus ryhmätyöstä.
Alle 15/25 pistettä tentistä.

Opiskelijalla on perusymmärrys tietosuojan sääntelystä ja tietää mistä löytää lisätietoja. Opiskelija tunnistaa tiedon suojaamisen teknisiä ratkaisuja.

Assessment criteria, good (3-4)

55%-85% henkilökohtaisista tehtävistä palautettu hyväksytysti.
55%-85% hyväksytty suoritus ryhmätyöstä.
Alle 20/25 pistettä tentistä.

Opiskelija tuntee tietosuojan sääntelyä sekä tuntee päätoimijoiden tehtävät ja vastuut. Opiskelija osaa suositella sopivia teknisiä ratkaisuja tiedon suojaamiseen sekä tietää miten toimitaan tietomurron sattuessa.

Assessment criteria, excellent (5)

>85% henkilökohtaisista tehtävistä palautettu hyväksytysti.
>85% hyväksytty suoritus ryhmätyöstä.
Yli 20/25 pistettä tentistä.

Opiskelija tuntee tietosuojan sääntelyä sekä tuntee päätoimijoiden tehtävät ja vastuut, minkä lisäksi ymmärtää edellytykset tiedon käsittelylle ja siirrolle. Opiskelija osaa suositella sopivia teknisiä ja hallinnollisia ratkaisuja tiedon suojaamiseen sekä toimia itsenäisesti tietomurron sattuessa. Opiskelija osaa arvioida tietosuojaa.

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

Mainly according to the book (from chapters 1-10)
[Aurélien Géron] Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, Publisher : O'Reilly Media; 2022, 3rd Edition

In addition: Material prepared by the teacher, online material and tasks in the learning environment.

International connections

The course includes approximately 12 guided working and theory sessions, 9 personal practice tasks and group work.
*
Group work is done in groups of 3-4 people outside of guidance sessions. The group sets aside 15 minutes outside of guidance sessions to present the group work.

Student workload

Contact hours:
- Course start-up: 2h
- Weeks 3 - 5: Theory & practice (3h/week): 5 x 3h = 15h
- Weeks 9 - 15: Theory & practice (3h/week): 7 x 3h = 21h
- Week 16: Project work presentations: 3h
- In addition, in weeks 4 - 15, about 10 support and inquiry hours: 10 x 1h = 10h

Total contact hours: about 51 hours

Independent study and homework: about 90 h

Content scheduling

Week 2:
- Machine learning landscape (Introduction to machine learning)
Weeks 3 - 7:
- End-to-end machine learning process
Weeks 9-15:
- Presentation of teamwork
- Classification
- Training linear models
- Decision trees
- Unsupervised learning
- Neural networks (Introduction to neural networks)
Week 16: Presentation of project works

Further information

The course materials and assignments are at ITS.
The exercises are mainly performed using Jupyter Notebook.
Communication about the course via ITS, but also via the course's Teams channel.

Evaluation scale

H-5

Assessment methods and criteria

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

You get points from the exercises n the contact class and homework, which affect the evaluation by 3 units.
About half of the exercises are done in contact classes.

The project work also affects the evaluation by 2 units. The project work is graded in ITS from 0 to 5, which is influenced by both the teacher's assessment and the peer assessment given by the rest of the project team.

The course can only be passed by doing both practice tasks and participating in project work.

Assessment criteria, fail (0)

The student does NOT participate in the project work or gets the project work grade 0 (Failed) OR did not get at least 40% 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 60-84% of the points for the exercises in the course AND got a grade of 3 - 4 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 can:

Describe what DevOps is and how it relates to software engineering,
Use tools and environments needed for DevOps,
Use DevOps in a software project.

Content

Basics of software production
DevOps model
Tools and Environments for DevOps
DevOps in practice
Project work

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

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 on 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 are provided after the completion of each task.

Student workload

classroom activities
individual work
pairwork
group work

Evaluation scale

H-5

Assessment criteria, fail (0)

The student has insufficient attendance. The student has not completed all the tasks. The student has completed tasks but they are not of an acceptable standard.

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.

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.

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.

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://cisco.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

After completing the course the student:
masters JavaScript and can use some of the most important libraries in developing browser user interfaces
can implement dynamic and responsive browser user interfaces that are usable in variety of devices
masters AJAX technology and JSON data-interchange format
can use efficient tools in browser scripting

Content

JavaScript
jQuery
Doing asynchronous requests with AJAX
JSON data-interchange format
Tools for developing browser interfaces
Implementing a small scale dynamic and responsive browser user interface

Materials

The course books (Selected parts)
*
Eloquent JavaScript
Marijn Haverbeke
No Starch Press; 3 edition (December 4, 2018)
Available on the Net: http://eloquentjavascript.net
*
Professional JavaScript for Web Developers
5th Edition
Matt Frisbie
Published by Wrox
Available in ProQuest EBook Central
*
Learning React : Modern Patterns for Developing React Apps
2nd edition
Alex Banks and Eve Porcello
Available in ProQuest EBook Central
*
Only selected chapters will be read.

Content scheduling

Contents

I. JavaScript (Lectures and personal exercises)

- Basics
- Strings
- Objects, destructuring
- Arrays, array operations
- Programming functions
- Error handling
- DOM, event handling
- Modules
- Asynchronous programming
- Tools

II. React (Lectures and a teamwork)

- Basics
- JSX
- Components
- Modularization
- Tools
- Managing state
- Hooks

III. Teamwork: A simple single page web application with React (without backend)

7 personal JavaScript exercises.
React-based Teamwork.

Evaluation scale

H-5

Assessment methods and criteria

7 personal assignments: 70 points
The group project work: 30 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.

The student must get at least 30 points from the assignments and 10 points from the group work to pass the course.

The grading scale (points b -> grade):

40 points -> 1
55 points -> 2
70 points -> 3
80 points -> 4
90 points -> 5

Objective

Deepening knowledge of 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

International connections

Practical assignments and reports
Project work
Self study

Completion alternatives

-

Student workload

Lectures and on-site activities: 86 hours
Assignments and self study: 66 hours
Project work 108 hours
Guest lectures + report: 10 hours
TOTAL 270 hours

Content scheduling

This course deepens project working skills on ICT field as well as substance knowledge of different ICT field -related topics. 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

Course material is in It´s Learning

Evaluation scale

H-5

Assessment methods and criteria

Course includes 6 assignments: 2 individual assignments and 4 group assignments. Maximum points of each assignment is 3 points. Thus, the maximum amount of points from assignments is 18.

In addition course includes 1 guest lecture report, which is assessed pass/fail.

Team work: formative assessment taking into account student's self and peer assessment.

Presence
50-59% attendance affect on your grade +0,1
60-64% attendance affect on your grade +0,2
65-69% attendance affect on your grade +0,3
70-74% attendance affect on you grade +0,4
75+% attendance affect on your grade +0,5

Final grade of the course is weighted average:
- Group assignments inc. self and peer assessment 40%
- Presence 10%
- Guest lecture report 10%
- Project work inc- self and peer assessment 40%

Assessment criteria, fail (0)

Less than 6 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: 6-7 points from assignments + passing guest lecture report + completing project work hours
Grade 2: 8-10 points from assignments + passing guest lecture report + 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: 11-13 points from assignments + passing guest lecture report + completing project work hours
Grade 4: 14-16 points from assignments + passing guest lecture report + 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: 17-18 point from assignments + passing guest lecture report + 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.

Objective

After completing the course the student:
- is able to explain the basic principles of information security testing and assessment
- can list the phases of information security testing process
- is able to organize and conduct information security risk testing to an SME sector enterprise or similar size organization
- can analyse and report the results from information security testing
- is able to give justified improvement proposals to mitigate information security vulnerabilities

Content

- Social Engineering
- Penetration Testing
- Network Discovery
- Network Service Identification
- Vulnerability Scanning
- Password Cracking

Materials

We are using the TryHackMe.com training platform in addition to ItsLearning. Licenses for the duration of the course will be provided.

Exam schedules

Practical exam is in late March / early April, with re-take chance in April.

Student workload

Lectures 8h
Laboratory assignments 27h
Homework 27h
Exam 3h
Testing project 70h

Content scheduling

Course begins with introductory lecture. In laboratory exercises student learns to use the tools of trade. Finally, students perform a penetration testing engagement and report the results.

Further information

All communication will be through ItsLearning.

Evaluation scale

H-5

Assessment methods and criteria

Laboratory and homework assignments 10-20% of grade
Exam 10-20% of grade
Project report 60-70% of grade

Assessment criteria, fail (0)

Student is unable to perform and report a penetration testing engagement independently.

Assessment criteria, satisfactory (1-2)

Student understands the basics of penetration testing and is able to perform a penetration test against a web application independently. Student can write an understandable and actionable report about the test results.

Assessment criteria, good (3-4)

Student has a good grasp of information security testing methodologies and tools. Student can independently test various types of internet connected applications. Student can write an understandable and actionable report about the test results that contains guidance for both the management and the developers responsible for the application.

Assessment criteria, excellent (5)

Student is has knowledge and is able to select the best suited tool and methodology for the engagement. Student can independently test most types of internet connected applications. Student can write a clear, concise and actionable report about the test results that effectively guides management decisions and provides the software developers with detailed guidance on both fixing to found issues and methods for avoiding similar issues in the future.

Qualifications

Courses Internet Networks and Security and Linux and Virtualization

Objective

After having completed the course, the student:
• can describe different topical areas of ICT, their interfaces to other fields and application opportunities from different perspectives
• can identify channels to contribute to the development of the society in general and own professional field in particular
• is familiar with the ICT degree programme's competence tracks' contents, applications and business cooperation
• analyze one’s own competences, interests, strengths and development areas

Content

* getting familiar with competence tracks' contents, laboratories, and projects
* career planning and choosing one's preference for competence track

Materials

Itslearning

Teaching methods

Lectures, practical work, reports etc.

Exam schedules

Taking the course requires attendance and finishing the given tasks. The is no chance for a retake after the course has ended.

International connections

Attendance & assignment requirements for each part are specified in Itslearning.
DEAI - Data Engineering and Artificial Intelligence
DNCS - Data Networks and Cybersecurity
EMB - Embedded Software and IoT
GAME - Game and Interactive Technologies
SEPM - Software Engineering and Project Management
EHEA - Health Technology

Completion alternatives

None

Student workload

Two weekly morning sessions per each part plus tasks / exercises.

Assessment criteria, approved/failed

To pass the course, students must pass 5/6 of the parts.

Content scheduling

The course consists of six parts, one for each competence track.
Lessons in Jan - April 2024, timetables for each group available in lukkari.turkuamk.fi.

Further information

Itslearning

Evaluation scale

Hyväksytty/Hylätty

Objective

After completing the course the student will be able to:
- Understand organizational functions and main business processes
- Describe business processes and process management principles
- Understand basic concepts of business operations and calculate key figures
- Identify different information management needs in business

Content

- Business plan
- Material-, information- and financial processes
- Business process management
- Business development

Materials

Materials created by the teacher, as well as an optional book/reading package.

Teaching methods

f2f training sessions, group work, personal reading, examination

Exam schedules

During the course, an exam will be held based on the lectures and other shared materials.

International connections

The course aims to introduce the student to the fundamentals of business through business development. Work involves developing a business idea, company, and its operations from both a strategic and operational perspective. Business development is done in small groups, and the output is presented, discussed, and evaluated in the form of a business plan. Students can tailor their own learning goals by choosing a business-related book or reading material of their interest. The exam aims to support the understanding of fundamental business concepts.

Student workload

Face-to-face instruction: 42 hours
Group work: 50 hours
Personal reading package: 30 hours
Exam: 10 hours

Content scheduling

weekly face-to-face training is delivered as introductory sessions and workshop work in small groups. Topics covered include, among others, product, customer segments, marketing communication, customer relationship management, data and goods flows, the concept of quality, business models, finance, and related concepts.

Evaluation scale

H-5

Assessment methods and criteria

The course grade is determined with the following weights:
50% for group work on business development presentations and final report (business plan)
25% for personal reading package
25% for personal exam

Group work requires personal initiative from the student, and peer feedback can be utilized in the assessment.

Assessment criteria, satisfactory (1-2)

The student uses key business terms and basic theories to report findings and observations. Can describe, classify, and list things. The output is descriptive but lacks reflection or insights. The student participates in group discussions.

Considerable guidance and support have been needed for the group's business idea planning. Collaboration within the group does not work or is difficult. Feedback has not been effectively utilized within the group. There are inconsistencies in the business plan, and it does not support the sale of the idea as desired. The course material and other sources have been used sparingly. The course concepts presented have not been applied in the plan. The plan is only partially feasible.

Assessment criteria, good (3-4)

The student understands the bigger picture and uses theory to describe it. Shows the ability to apply a principle related to the topic and can combine ideas. Utilizes acquired material in their own and group work. Participates in group discussions, is active in creating the business plan, and takes responsibility for group tasks.

The group's business idea is quite creative. It has been planned independently and in consensus with the entire group. The business plan is a clear and consistent document. The application of course concepts to their own business plan demonstrates expertise. The plan is largely feasible. The presentation is clear, understandable, and persuasive.

Assessment criteria, excellent (5)

The student identifies critical success factors for the industry and company, understands theory, and presents their findings with justification. Can identify areas for improvement and is a critical thinker. Can analyze cause-and-effect relationships and handle issues insightfully. High-quality background material has been independently sought and found, and its use is justified. The student actively, proactively, and responsibly participates in group discussions and takes the group's knowledge to a deeper level.

The group's business idea is innovative and creative. It has been planned enthusiastically, responsibly, and in consensus with the entire group. Various sources and course materials have been used extensively. The business plan and presentation are clear, understandable, consistent, persuasive, and creative. The plan is for most parts feasible.

Evaluation scale

H-5

Assessment methods and criteria

Course grading will be based on home assignments and laboratory assignments.

On-site course attendance is required minimum 50% to pass the course. Exceptions are to be agreed with the Lecturer individually.

Maximum points score (excl. bonus labs) for the course is 100p, and grading is as follows:

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

Objective

After completing the course the student can:
- describe different software development methodologies and evaluate their feasibility to software projects

- describe software development project phases

- understand and draw UML diagrams

- understand the importance of specification and planning to software development

- work in different phases of a software project

Content

- Software development project

- Specification, planning, programming, testing, deployment, and maintenance of a software project

- UML modelling

Materials

Erikseen jaettavat ja linkatut lähiopetuskertojen materiaalit, ohjelmistotyökalut, dokumentointipohjat.

Teaching methods

Opintojaksolla harjoitellaan toimimista ohjelmistoprojektin eri vaiheissa.
Harjoitustyönä toteutetaan ryhmässä hallittu ohjelmistoprojekti alusta loppuun: Ohjelmiston määrittely, suunnittelu, ohjelmointi, testaus, ja käyttöönotto.

International connections

Harjoitustyö toteutetaan ryhmässä. Projektissa noudatetaan SCRUM menetelmän periaatteita. Viikoittaisilla opetuskerroilla tehdään ohjelmistuotantoon liittyviä pienempiä tehtäviä, jotka palvelevat harjoitustyön tekemisen osia sekä edistetään omaa harjoitustyöprojektia.

Student workload

Opintojakson laajuus on 5 opintopistettä.
Työmäärä on 5 * 27 tuntia eli 135 tuntia.
Opintojakson kesto on noin 14 viikkoa.
Viikottainen työmäärä on noin 10 tuntia, josta
viikkoharjoitukset noin 2 tuntia ja oma harjoitustyönä oleva
ohjelmistoprojekti noin 8 tuntia.

Content scheduling

Opintojakson suoritettuaan opiskelija :
- tuntee ohjelmistoprojektimalleja ja arvioida niiden soveltuvuutta ohjelmistoprojekteihin
- osaa toimia ohjelmistoprojektin eri vaiheissa ja rooleissa
- ymmärtää määrittelyn, suunnittelun ja testauksen merkityksen ohjelmistoprojektissa
- osaa laatia ohjelmistotuotannossa käytettyjä suunnittelukaavioita (UML), käyttöliittymäprototyyppejä ja käyttää versionhallintaa yhteistyössä muiden kanssa
- käyttää ketterää kehitystä tukevaa työkalua ohjelmistoprojektin ja vaatimustenhallintaan

Further information

Osallistumisen edellytyksenä ovat perustaidot jostakin ohjelmointikielestä. Kurssilla toteutetaan ryhmätyönä ohjelmisto, mutta ohjelmoinnin opetus ei ole varsinaisesti kurssin sisältöä.

Evaluation scale

H-5

Assessment methods and criteria

Harjoitustyö muodostaa 60 % arvosanasta. Opintojaksosta läpipääsy edellyttää hyväksytysti suoritettua harjoitustyötä
Aktiivinen osallistuminen lähiopetukseen muodostaa 40 % arvosanasta
Harjoitustyön välipalautukset (sprinttien tuotokset) arvostellaan pistein 0-2, jossa:
2 pistettä: Erittäin hyvä (tehtävät palautettu ajoissa, tehty tehtävänannon mukaisesti, ei puutteita)
1 piste: Hyväksytty (tehtävät palautettu ajoissa, tehty tehtävänannon mukaisesti, pienehköjä puutteita)
0 pistettä: Hylätty (tehtäviä ei palautettu ollenkaan, osa tehtävistä puuttuu, tehtävät palautettu myöhässä tai tehtävät ovat erittäin puutteellisia)
Lähiopetukseen osallistumisesta saa 1 pisteen / kerta. Pisteen saaminen edellyttää aktiivista osallistumista ja tehtävien tekemistä lähiopetustunteihin liittyen. Niinä kertoina, kun erillistä oppituntitehtävää ei ole, pisteen saa läsnäolosta. Läsnäolot kerätään joka oppitunnilla, mutta ainoastaan tehtävittöminä oppituntikertoina niistä saa suoraan pisteen.
Kurssin arvosana muodostuu seuraavasti:
Harjoitustyön pistemäärä = arvosana: 0-5p. = 0, 6-8p. = 1, 9-10p. = 2, 11-12p. = 3
Lähiopetuksen pistemäärä = arvosana lisäys: 0-6p. = +0; 7-10p. = +1; 11p. tai enemmän = +2 harjoitustyön arvosanaan. Jos jostain syystä yhteenlasketut maksimipistemäärät poikkeavat yllä olevista, kertyneet pisteet skaalataan yllä ilmoitetulle välille lineaarisesti.

Objective

After completing the course the student can:
- describe the most important software application types and their typical features
- discuss the selection of a proper solution technology
- define the main concepts of programming such as source code, compiler, variable and data type
- read program code written by someone else
- utilize the most important decision and control structures
- recognize basic object-oriented concepts (class and its members, object, reference, exceptions)
- design and implement simple software applications
- draw a flow chart of the program.

Content

- software application structure
- development environment and tools
- variables and data types
- functions
- decision and control structures
- arrays and lists

Materials

Kaikki oppimateriaali ilmoitetaan ItsLearningissä.

Teaching methods

Opintojaksolla opetellaan uudet asiat ensin opettaja-vetoisesti. Opettaja esittelee teoreettisen taustan. Sen jälkeen opettaja näyttää omalta koneelta ohjelmoiden, miten uusi opiskeltava asia tuodaan ohjelmointitehtäviin. Opiskelijat tekevät saman ohjelmointiharjoituksen omalla koneellaan.

Tämän jälkeen opettaja antaa opiskelijoille harjoitustehtäviä, joissa pääpaino on opiskeltavassa asiassa. Sen jälkeen jatketaan harjoitustehtävillä, joissa uusi asia integroidaan jo opittuihin asioihin. Kun opiskelijat tekevät harjoitustehtäviä, molemmat opettajat ovat opiskelijoiden tukena.

Exam schedules

Opintojaksolla ei ole tenttiä.

International connections

Opintojaksolla opetellaan uudet asiat ensin opettaja-vetoisesti. Opettaja esittelee teoreettisen taustan. Sen jälkeen opettaja näyttää omalta koneelta ohjelmoiden, miten uusi opiskeltava asia tuodaan ohjelmointitehtäviin. Opiskelijat tekevät saman ohjelmointiharjoituksen omalla koneellaan.

Tämän jälkeen opettaja antaa opiskelijoille harjoitustehtäviä, joissa pääpaino on opiskeltavassa asiassa. Sen jälkeen jatketaan harjoitustehtävillä, joissa uusi asia integroidaan jo opittuihin asioihin. Kun opiskelijat tekevät harjoitustehtäviä, molemmat opettajat ovat opiskelijoiden tukena.

Completion alternatives

1) Antamalla näytön esim. tekemästään työelämän projektista, jolla opiskelija osoittaa hallitsevansa opintojakson sisällön.
2) Sivustolla mooc.fi kuvataan ohjelmoinnin MOOC, joka vastaa sisällöltään Helsingin yliopiston tietojenkäsittelytieteen laitoksen kursseja Ohjelmoinnin perusteet ja Ohjelmoinnin jatkokurssi. Kurssit vastaavat yhteensä kymmentä opintopistettä (5+5).
Ohjelmoinnin perusteet voi suorittaa tekemällä ohjelmoinnin MOOCin alkuosan.

Student workload

Opiskelijan työn mitoitus

5 opintopistettä: 27 * 5 = 135 tuntia

Opintojakson kesto: 8.1. - 19.4.2024 (14 viikkoa + opetukseton viikko 8)

Viikkotyömäärä: 135 tuntia / 14 viikkoa = 9,5 tuntia viikossa

Content scheduling

Opintojaksolla opiskellaan ohjelmoinnin ajattelutapaa sekä tutustutaan ohjelmistokehityksen pääpiirteisiin.

Opintojakson harjoitukset tehdään Javalla.

Tulostaminen näytölle ja tiedostoon.
Tiedon lukeminen näppäimistöltä ja tiedostosta.
Ohjelmoinnin valintarakenteet.
Ohjelmoinnin toistorakenteet.
Aliohjelmat ja niiden käyttö.
Poikkeukset.
Taulukot ja merkkijonot.
Ohjelman dokumentointi.
Ohjelman testaus.

Further information

Kurssin viestintä tapahtuu pääsääntöisesti ItsLearningissä.

Evaluation scale

H-5

Assessment methods and criteria

Opintojakson läpäisy edellyttää hyväksytysti suoritettujen harjoitusten tekemistä sekä aktiivista osallistumista harjoitustyön tekoon.

Viikkokohtaisia kotitehtäviä on 10 sarjaa, kussakin 10 pisteen edestä tehtäviä. Kotitehtäväsarjan kokonaisarviointi noudattaa seuraavaa kaavaa:
40 pistettä -> 1
55 pistettä -> 2
70 pistettä -> 3
80 pistettä -> 4
90 pistettä -> 5

Harjoitustyö arvioidaan erikseen skaalalla 1-5.

Opiskelijan opintojakson arvosana muodostuu kotitehtäväsarjan ja harjoitustyön keskiarvosta. Molempien osioiden pitää olla hyväksyttyjä.

Assessment criteria, fail (0)

Hyväksytysti suoritettuja harjoituksia puuttuu ja/tai harjoitustyö puuttuu.

Assessment criteria, satisfactory (1-2)

Hyväksytysti suoritettuja harjoituksia on tehty minimimäärä tai niiden laatu on tyydyttävä ja/tai harjoitustyön laatu on tyydyttävää tasoa.

Assessment criteria, good (3-4)

Hyväksytysti suoritettuja harjoituksia on tehty riittävästi ja niiden laatu on hyvää ja harjoitustyön laatu on hyvää tasoa.

Assessment criteria, excellent (5)

Hyväksytysti suoritettuja harjoituksia on tehty maksimimäärä ja niiden laatu on kiitettävää ja harjoitustyön laatu on kiitettävää tasoa.

Qualifications

Basic computer skills and high school or vocational school mathematics curriculum or equivalent skills.

Objective

After completing the course the student can:
- explain the different phases and main methods of the development of a software product
- explain the concepts class hierarchy, inheritance, and polymorphism, and utilize these in software development
- discuss the possibilities of parallel programming
- apply exception handling mechanisms
- design, implement and document a simple user interface application.

Content

- object-oriented structures
- error handling with exceptions
- threads
- database connection
- software development process and methods
- UML diagrams

Evaluation scale

H-5

Qualifications

Introduction to Programming or equivalent programming skills

Objective

After completing the course the student can:
- explain the different phases and main methods of the development of a software product
- explain the concepts class hierarchy, inheritance, and polymorphism, and utilize these in software development
- discuss the possibilities of parallel programming
- apply exception handling mechanisms
- design, implement and document a simple user interface application.

Content

- object-oriented structures
- error handling with exceptions
- threads
- database connection
- software development process and methods
- UML diagrams

Materials

All the learning materials are mentioned in ItsLearning

Teaching methods

The course is structured as separate lectures and demo sessions. During the lectures, the teacher will go through the theory and the students are coding some exercises together with the teacher using their own computers.

Reading the given material and coding the programming exercises and exercise work.

Demonstrating and documenting the exercises and exercise work.

Exam schedules

There is no exam in this course

International connections

Self assessment
Student regularly pays attention to own learning and studying.
Students are asked to take notes from each programming exercise and contemplate at least the following:
* Topic area: What did I know about the topic beforehand? What did I think about the area?
* While coding: Thoughts about the challenge level and interest of the exercise.
* Afterwards: What did I learn?

Moreover, students learn to assess their own work regarding every assignment using scale: Excellent - Good - Sufficient.

Completion alternatives

1) Demonstrate e.g. a real work life project and showing that student masters the contents of this course.

2) mooc.fi contains a programming MOOC, whose contents covers the Introduction to Programming and Advanced Programming courses of the University of Helsinki. Courses are 10 credits together (5+5). Object oriented course can be alternatively completed by completing the second part of the course (i.e., parts 8 to 14).

Student workload

To pass this course requires acceptably finished coding exercises as well as exercise work and return in time.

5 credits: 27 * 5 = 135 hours

Weekly work amount: 135 hours / 14 weeks = 9.5 hours a week.

Content scheduling

The exercises in this course are done with Python

Objective
After completing the course the student can:
- explain the different phases and main methods of the development of a software product
- explain the concepts class hierarchy, inheritance, and polymorphism, and utilize these in software development
- discuss the possibilities of parallel programming
- apply exception handling mechanisms
- design, implement and document a simple user interface application.

Content
- object-oriented structures
- error handling with exceptions
- threads
- database connection
- software development process and methods
- UML diagrams

Further information

The main information channel is ItsLearning

Evaluation scale

H-5

Assessment methods and criteria

The course contains 8 weekly exercises and an exercise work (that corresponds 4 weekly exercises). They can contain both programming theory and coding.

Each exercise has several tasks, from which points are given. Maksimum points from each exercise is 10 and from all exercises is 120.

Grade is formed based on the number and quality of acceptably finished exercises and the presence at class:

less than 60 points -> grade 0
60 points -> grade 1
72 points -> grade 2
84 points -> grade 3
96 points -> grade 4
108 points -> grade 5
Presence less than 75 % on the Friday lectures (without an acceptable reason) reduces the exercise points by 10%.
Acceptable reason to skip lectures is illness (or sudden tragedy in immediate family). Please inform teacher in advance if you cannot make it to the lecture. Working or holiday trip etc. are not acceptable reasons for absence.

Assessment criteria, fail (0)

Grade is fail if less than 60 points is achieved from exercises and/or exercises are very insufficient or of very poor quality.

Assessment criteria, satisfactory (1-2)

Grade is satisfactory (1-2) if 60 - 71 points is achieved and exercises are done in time. Exercises may contain minor (quality) issues.

Assessment criteria, good (3-4)

Grade is good (3-4) if 72 - 107 points is achieved, exercises are done in time and they are well done.

Assessment criteria, excellent (5)

Grade is excellent (5) if at least 108 points is achieved, exercises are done in time and the quality is excellent.

Objective

After completing the course the student is able to:
- describebasic tasks and concepts of operating systems
- install and configure an operating system for desktop and server
- act as operating systems administrator

Content

- Operating system tasks and concepts
- Installing and configuring operating system for desktops and servers
- System administrating using command line interface
- User access management
- Server installation and management

Materials

I . Kurssikirjat:

The Linux Command Line: A Complete Introduction
William Shotts
2nd edition
2019
Tästä on olemassa netissä vielä uudempi, päivitetty painos: https://linuxcommand.org/tlcl.php

Mastering Ubuntu Server
Jay LaCroix
4th edition
2022

Kurssikirjoja luetaan vain valikoiduin osin.

Kurssikirjat ovat luettavissa oppilaitoksemme eBook Central -palvelussa.

II. Teoreaosuuden tutoriaali

Operating System Tutorial: https://www.tutorialspoint.com/operating_system/index.htm

III. Opettajan laatimat harjoitustehtävät.

Exam schedules

Kurssin puolen välin jälkeen monivalintatentti käyttöjärjestelmien teoriasta.

Uusintamahdollisuus kurssin päätteeksi.

International connections

Käytännön työskentely luokassa opettajan johdolla
Pääosin kotona tehtävät käytännön harjoitustehtävät
Käyttöjärjestelmien teoria: esitelmän pitäminen ryhmässä
Materiaalin lukeminen
Tenttiminen

Student workload

Käytännön opetusta paikan päällä 24h
Teoriaa paikan päällä sisältäen esitelmän ryhmässä10h
Tentti ja sen uusintatilaisuus 4 h
Oman virtuaaliympäristön valmistelua ja ylläpitoä 7h
Materiaalin läpikäyntiä ja harjoitustehtävien tekemistä 70h
Tenttiin valmistautumista 20h

Content scheduling

Käytännön opetus etenee pääpiirteissään seuraavassa järjestyksessä:

Linux-käyttöjärjestelmän asentaminen virtuaalikuvakkeelle
Johdatus käyttöjärjestelmiin
Bash-komentotulkin peruskäyttö
Pääkäyttäjänä toimiminen
Ohjelmistojen ja prosessien hallinta
Käyttäjien ja oikeuksien hallinta
Bash-komentotulkin kehittyneempi käyttö
Verkkoyhteyksien hallinta
Johdatus palvelimiin
Tietokantapalvelimen asentaminen
Web-palvelimen asentaminen ja hallitseminen
Tietoturvan perusteita

Teoriaopetus etenee pääpiirteissään seuraavasti

Harjoitustyö: esitelmä ryhmässä teoria-aiheesta
Muiden esitelmien seurantaa ja teoriaan perehtymistä tutoriaalin perusteella
Teoriatentti ja sen uusinta.

Evaluation scale

H-5

Assessment methods and criteria

Käytännön osuuden arvosteluskaala (harjoitustehtävät): vähintään 30 pistettä -> 0,5 arvosanayksikköä; 38 pistettä -> 1,0; 46 pistettä -> 1,5; 54 pistettä -> 2,0; 62 pistettä -> 2,5; 70 pistettä -> 3,0. Maksimipistemäärä 80. (Alin hyväksytty suoritus 0,5 arvosanayksikköä)

Harjoitustehtävät tarkistetaan demoiksi ilmoitetuilla luennoilla. Niillä on oltava läsnä. Poissaolosta seuraa 25 prosentin pistevähennys.

Teoriaosuus: harjoitustyö ryhmässä 10 pistettä ja tentti 20 pistettä.

Teoriaosuuden arvosteluskaala: vähintään 12 pistettä -> 0,5 arvosanayksikköä; 16 pistettä -> 1,0; 20 pistettä -> 1,5; 24 pistettä -> 2,0. Maksimipistemäärä 30. 0,0-2,0 (Alin hyväksytty suoritus 0,5 arvosanayksikköä)

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.

Evaluation scale

H-5

Objective

After completing the course the student is able to:
- Describe how different ICT services and solutions relate to enterprise’s business operations.
- Describe an activity as algorithm (process) as input for “software program”.
- Make working software program (application) with selected programming language.
- Use the techniques available when creating internet pages.
- Develop responsive web applications.
- Identify principles of usability and apply them when developing user interfaces.
- Understand how internet page browser works and use some tools when developing internet pages.

Content

Introduction to Business Operations.
Introduction to programming.
Introduction to the development of responsive internet user interfaces.

Evaluation scale

H-5

Objective

After completing the course the student is able to:
- Work as a member of a project team and describe how ICT projects are managed.
- Document and report project results.
- Utilize different environments and platforms for learning.
- Use the techniques available when creating internet pages, and create working www-page using them.
- Use Information Technology tools when working in project.
- Describe what specialization options are available in Business IT program.
- Be familiar with the ICT degree programme's competence tracks' contents, applications and business cooperation.
- Analyze one’s own competences, interests, strengths and development areas.

Content

Introduction to Project Management.
Introduction to Version Control.
Practical project work.
Getting familiar with competence tracks' contents, laboratories, and projects.
Career planning and choosing one's preference for competence track.

Evaluation scale

H-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.
Use some cloud services platforms.
Develops 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

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.

International connections

FLIP classrooms and learning by doing

Completion alternatives

Ask the teacher about possible alternative methods of execution

Student workload

135h

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

Further information

Course material and assignments in Its Learning.

Evaluation scale

H-5

Assessment methods and criteria

9 personal assignments/Labs: 90 points
Presentation demonstration of assignments: 10 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.

The student must be present in the demos (on the lectures where the personal assignments are checked and presented).

The grading scale (points -> grade):

40 points -> 1
55 points -> 2
70 points -> 3
80 points -> 4
90 points -> 5

Objective

After completing the course the student can:
Describe different project management methods and frameworks and their feasibility to different projects.
Ability to function as a project manager in different phases of a project and produce the project related specifications and documents.
Describe different project management association and certifications.
Risk analysis and quality assurance.

Content

The course covers aspects of different project management methods, such as waterfall and agile as well as different project management associations and certifications. Furthermore, the course covers topics about project management, including project planning, budgeting, scheduling and WBS, risk assessment and quality assurance.

Materials

Various internet sources, links & descriptions online

Teaching methods

Lectures, group work and independent work, project work, online activities

Exam schedules

-

International connections

Practical assignments and reports
Project work
Self study

Completion alternatives

-

Student workload

Lectures and on-site activities: 54 hours
Assignments and self study: 71 hours
Guest lectures + report: 10 hours
TOTAL 135 hours

Content scheduling

The course starts with the course introduction and team building followed by Scrum simulation. The focus is set on agile project management, especially Scrum framework. There after the aspects of waterfall project management methodology are discussed. The student learns how to create a realistic project plan, budget, timeframe and risks for the project. In addition, student learns setting up goals for the project that create customer value, resource allocation and division of work and sizing. IPMA International Project Management Association and other project management institutions and activities are presented as well as IPMA standards – Individual Competence Baseline. Students also practice risk management and risk analysis in more detail. Lastly, quality management in software engineering is handled in lectures and group work.

Further information

Course material is in It´s Learning

Evaluation scale

H-5

Assessment methods and criteria

Assignments and reports: diagnostic assessment.

Course includes 7 assignments: 2 individual assignments and 5 group assignments. Maximum points of each assignment is 3 points. Thus, the maximum amount of points from assignments is 21.

In addition course includes 1 guest lecture report, which is assessed pass/fail.

Team work: formative assessment taking into account student's self and peer assessment.

Presence
50-59% attendance affect on your grade +0,1
60-64% attendance affect on your grade +0,2
65-69% attendance affect on your grade +0,3
70-74% attendance affect on you grade +0,4
75+% attendance affect on your grade +0,5

Final grade of the course is weighted average:
- Assignments 80%
- Presence 10%
- Guest lecture report 10%
- Self- and peer assessment is taken into account

Assessment criteria, fail (0)

Less than 7 points from assignments

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

Assessment criteria, satisfactory (1-2)

Grade 1: 7-9 points from assignments + passing guest lecture report
Grade 2: 10-12 points from assignments + passing guest lecture report

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

Assessment criteria, good (3-4)

Grade 3: 13-15 points from assignments + passing guest lecture report
Grade 4: 16-18 points from assignments + passing guest lecture report

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

Assessment criteria, excellent (5)

Grade 5: 19-21 point from assignments + passing guest lecture report

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

Objective

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

· Configure VLANs and Inter-VLAN routing applying security best practices.
· Troubleshoot inter-VLAN routing on Layer 3 devices.
· Configure redundancy on a switched network using STP and EtherChannel.
· Troubleshoot EtherChannel on switched networks.
· Explain how to support available and reliable networks using dynamic addressing and first-hop redundancy protocols.
· Configure dynamic address allocation in IPv6 networks.
· Configure WLANs using a WLC and L2 security best practices.
· Configure switch security to mitigate LAN attacks.
· Configure IPv4 and IPv6 static routing on routers.

Content

CCNAv7: Switching, Routing, and Wireless Essentials (SRWE) covers the architecture, components, and operations of routers and switches in small networks and introduces wireless local area networks (WLAN) and security concepts. Students learn how to configure and troubleshoot routers and switches for advanced functionality using security best practices and resolve common issues with protocols in both IPv4 and IPv6 networks. 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://cisco.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 covers the architecture, components, and operations of routers and switches in small networks and introduces wireless local area networks (WLAN) and security concepts. Students learn how to configure and troubleshoot routers and switches for advanced functionality using security best practices and resolve common issues with protocols in both IPv4 and IPv6 networks. The course includes activities using Packet Tracer, hands-on lab work, and a wide array of assessment types and tools. By the end of the course, students will be able to:

- Configure VLANs and Inter-VLAN routing applying security best practices.
- Troubleshoot inter-VLAN routing on Layer 3 devices.
- Configure redundancy on a switched network using STP and EtherChannel.
- Troubleshoot EtherChannel on switched networks.
- Explain how to support available and reliable networks using dynamic addressing and first-hop redundancy protocols.
- Configure dynamic address allocation in IPv6 networks.
- Configure WLANs using a WLC and L2 security best practices.
- Configure switch security to mitigate LAN attacks.
- Configure IPv4 and IPv6 static routing on routers.

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 (TE00BU11) or equivalent skills.

Objective

After completing the course the student is able to:
- Write in a formal manner
- Maintain, improve, and critically evaluate his/her communicative skills
- Function in a planned and focused manner in different oral communication situations
- Strive for improving and critically evaluating his/her communicative skills, and give  constructive criticisms
- Know the principles of the organizational communication and public relations.

Content

Contents
- Principles of writing in a formal style
- Oral communication and grammar
- Organizational communication and public relations

Evaluation scale

H-5

Objective

After completing the course the student is able to:
- Write in a formal manner
- Maintain, improve, and critically evaluate his/her communicative skills
- Function in a planned and focused manner in different oral communication situations
- Strive for improving and critically evaluating his/her communicative skills, and give  constructive criticisms
- Know the principles of the organizational communication and public relations.

Content

Contents
- Principles of writing in a formal style
- Oral communication and grammar
- Organizational communication and public relations

Evaluation scale

H-5

Objective

The student can communicate orally in different work-life situations.

Content

The student
- can describe the content and structure of his/her studies, training and work experience
- can describe his/her working environment and operations of a company, products and processes
- can communicate in various business life situations appropriately
- is able to use appropriate vocabulary and phrases when presenting tasks of his/her own field

Materials

Lecturer's material in ITSlearning

Teaching methods

- contact/online lessons
- online studies
- video-cv

Content scheduling

Contents:
- education
- employment
- numerical expressions
- telephoning and sending e-mail
- IT vocabulary and current topics

Evaluation scale

H-5

Assessment methods and criteria

Englanniksi
0-5. The grade is based on active participation in lessons, oral assignments and an interview.

Objective

The student can communicate in writing in different work-life situations.

Content

The student
- can describe the content and structure of his/her studies, training and work experience
- can describe his/her working environment and operations of a company, products and processes
- can communicate in various business life situations appropriately
- is able to use appropriate vocabulary and phrases when presenting tasks of his/her own field

Materials

- lecturer's material in Itslearning

Exam schedules

written exam

International connections

- lectures and online lessons in Zoom
- written assignments
- online studies

Content scheduling

Contents:
- describing your education
- work experience and CV
- IT vocabulary and current topics in technology
- telephoning and writing email

Evaluation scale

H-5

Assessment methods and criteria

0-5. The grade is based on active participation in contact lessons, written assignments, 1-2 word tests and a written exam.

Objective

After completing the course the student can:
Act as a sales person in demanding technical sales.
Sell complicated technical solutions.
Lead sales project.

Materials

Internet sources, links & descriptions online

Teaching methods

Lectures, team work, independent work and online activities

Exam schedules

No exam

International connections

Practical assignments and reports
Team work
Self study

Completion alternatives

No optional ways for implementation

Student workload

Lectures and on-site activities: 72 h
Assignments and self study 63 h
TOTAL 135 hours

Content scheduling

The course starts with different aspects of tehnical sales. The student learns how to match technology and business, understand the customer needs and busines cases. There after different kinds of marketing and sales strategies and processes are presented as well as offers and contracts. After that, the focus is set on account management. Last, business ethics is handled in lectures and team work.

After the course students have a clear understanding of technical sales as part of the work of the future.

Further information

Course material and assignments are in It´s Learning

Evaluation scale

H-5

Assessment methods and criteria

Assignments and reports: diagnostic assessment.

Course includes 6 assignments: 2 individual assignments and 4 group assignments. Maximum points of each assignment is 3 points. Thus, the maximum amount of points from individual assignments is 6 points and 12 points from group assignments.

Team work: formative assessment taking into account student's self and peer assessment.

Presence
50-59% attendance affect on your grade +0,1
60-64% attendance affect on your grade +0,2
65-69% attendance affect on your grade +0,3
70-74% attendance affect on you grade +0,4
75+% attendance affect on your grade +0,5

Final grade of the course is weighted average:
- Individual assignments inc. self assessment 30%
- Group assignments inc. self and peer assessment 60%
- Presence 10%

Assessment criteria, fail (0)

Less than 4 points from group assignments
Less than 2 points from individual assignments

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

Assessment criteria, satisfactory (1-2)

Grade 1:
- 4 points from group assignments
- 2 points from individual assignments

Grade 2:
- 5-6 points from group assignments
- 3 points from individual assignments

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

Assessment criteria, good (3-4)

Grade 3:
- 7-8 points from group assignments
- 4 points from individual assignments

Grade 4:
- 9-10 points from group assignments
- 5 points from individual assignments

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

Assessment criteria, excellent (5)

Grade 5:
- 11-12 points from group assignments
- 6 points from group assignments

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

Qualifications

Technical solution selling.
Project selling.
Special issues in selling complicated technical solutions.

Objective

After completing the course, the student can:

Describe what artifical intelligence (AI) is about and how to build solutions that utilise artificial intelligence.

Content

Basics of AI
Recap of Machine Learning
Examples of solutions utilizing AI

Evaluation scale

H-5

Objective

After completing the course the student is able to:
- Perform calculations in different numbering systems
- Make conversions between the numbering systems
- Represent logical expressions with Boolean algebra and use it for problem solving
- Utilize probability calculations in problem solving
- Analyse data with statistics
- Utilize tools when analysing data and performing mathematical calculations

Content

- Numbering systems and binary calculations
- Boolean algebra and logical operations
- Introduction to Probability Calculation
- Introduction to Business Mathematics
- Introduction to Statistics and Data Analysis

Evaluation scale

H-5

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
Internet material about SQL and noSQL

Teaching methods

The course consists of 1) exercises (db queries and design tasks) 2) practical work tasks and 3) exam. Exercises are divided into weekly topics. These are practiced both individually and with the help of the teacher in the session. Each session begins with an introduction to the topic of the week, which includes practical examples with lecture slides.

Exam schedules

The exam is performed in Ville system.
1st exam is organized in the class room (during the regular meeting time) where Internet use is allowed for information retrieval. 2nd and 3rd exams as e-exams in the aquarium premises where Internet use is not allowed. E-exams are open the rest of the year.

International connections

Learning by doing, trial-error, listening carefully the teacher, and collaborating with other students, self- and peer-assessments.

Completion alternatives

Participation in the teaching session is not compulsory, but highly recommended. Each week we introduce a new topic that builds on top of previous weeks.

Remote self-studying in online mode is possible (with slightly different emphasis in topics and grading, announced in the beginning of the course).

Student workload

Recommended 8 hours / week for lectures, solving exercises and practical work tasks, if you are new to relational databases.

Participating weekly in teaching sessions: a' 3 hours * 14 =42h
Individual work:
for exercises 50h
Practical work 30h
Exam 10h

Content scheduling

In this course, students learn to use and design relational databases as well as understand differences to document databases.
Weekly meetings.Topics (and hours used in teaching sessions):
- Relational DBMS and DB use 4h
- Basics of SQL 13h
- Relational database design 7h
- Introduction to document database MongoDB 4h

Further information

We will use a DBMS environment for practical training (MySQL), which needs installation on the personal computer.
Highly likely, the environment for using DBMS is some LAMP stack with graphical UI like UwAmp, but you can use similar like XAMPP.
In addition to DBMS environment, we will use MongoDB cloud for practicing document databases.

Evaluation scale

H-5

Assessment methods and criteria

The course is graded from 0-5. The grade is based on collected points.
Each exercise is 1 point unless mentioned otherwise. The exam must be passed.

Exercises: 65 points,
Practical work: 55 points
Exam 70 points;
Total 190 points

Grading by points:
Points Grade
0-89 NOT PASSED
90-107 1
108-124 2
125-144 3
145-159 4
160-190 5

Objective

After completing the course the student is able to:
- name and explain the basic principles of Information Security
- describe the importance of information security for operations in organization
- name and describe the devices and services used to support communications in data networks and the Internet
- describe the importance of addressing and naming schemes at various layers of data networks in IPv4 and IPv6 environments
- design, calculate, and apply addresses and subnet masks to fulfill given requirements in IPv4 and IPv6 networks
- build a simple Internet network using wireless devices, routers and switches
- use basic configuration commands to design, configure and manage basic networks.

Content

- basic principles of Information Security
- use and importance of information security for operations in organization
- network terminology, Network protocols, Packet Tracer
- IP-addressing and Subnetting, IPv4 and IPv6
- network devices hardware and software
- building Wireless and Wired Local Area Network
- building a Connected Network

Materials

Materiaalit jaetaan Itslearning-alustan kautta.

Teaching methods

Luennot, demot, laboratoriotyöskentely, Itsenäinen opiskelu.

Exam schedules

Tietoverkko-osiossa ja tietoturvaosiossa on kummassakin osakoe osion päättyessä. Molemmissa osakokeissa on kaksi erillistä suoritusmahdollisuutta, osakoetta ei voi uusia.

International connections

Lähiopetus.
Opetusmateriaali on englanninkielistä.

Completion alternatives

Vastaavan tietomäärän osoittaminen aiemmilla koulutuksilla tai sertifikaateilla. Taitokoe.

Student workload

Luennot ja demot 10x2h = 20h
Laboratoriotyöt 6x3h=18h
Kotitehtävät ja itseopiskelu = 68h
Osakokeisiin valmistautuminen = 20h
Osakokeet 2 x 2h = 4h

Yhteensä 130h

Content scheduling

Tietoverkot periodilla S1 ja Tietoturva periodilla S2 (alustava arvio, voi muuttua kurssin alkaessa)

Further information

Opiskelija tarvitsee oman tietokoneen, jolla voi ajaa intel-arkkitehtuurin virtuaalikoneita. Lisäksi on suositeltavaa hankkia oma USB-ethernet adapteri jos koneessa ei ole kiinteää ethernet-liitäntää.
Materiaalien jako ja kurssin muu tiedottaminen tapahtuu Itslearning-alustan kautta.

Evaluation scale

H-5

Assessment methods and criteria

Demotehtävät ja laboratoriotyöt / tietoverkot 25p
Osakoe / tietoverkot 25p

Demotehtävät ja laboratoriotyöt / tietoturva 25p
Osakoe / tietoturva 25p

Yhteensä 100p

Assessment criteria, fail (0)

Opiskelija ei tunne alan peruskäsitteitä.
Osasuorituksista alle 50 pistettä

Assessment criteria, satisfactory (1-2)

Opiskelija tuntee jossain määrin peruskäsitteitä.
Osasuorituksista 50-69 pistettä

Assessment criteria, good (3-4)

Opiskelija tuntee melko hyvin peruskäsitteitä.
Osasuorituksista 70-89 pistettä

Assessment criteria, excellent (5)

Opiskelija tuntee erittäin hyvin peruskäsitteet ja osaa soveltaa tietojansa verkkojen tietoturvan perustarpeisiin.
Osasuorituksista 90 pistettä tai enemmän

Materials

Materials in Itslearning

Teaching methods

contact teaching, task-based learning, independent study

Exam schedules

N/A

International connections

The course covers the basic skills of research communication and goes through the thesis process.

Completion alternatives

No alternative methods of attainment

Student workload

The course schedule will be published in Itslearning. Instruction in Finnish and instruction in English in alternate weeks. Typically, the course has 13 sessions (1 x kickoff to the course, 6 x classes in English, 6x classes in Finnish)
Contact classes: 2 x 14h = 28h (14h in Finnish, 14 h in English)
Students' own work : 31h
Students can attend either Finnish or English or both language sessions. However, it is recommended that they attend the classes in the language in which they will write their thesis.

Assessment criteria, approved/failed

Approved: active attendance at least 5 Researc Communication lessons and attendance at least 2 Thesis seminars and a topic paper done.
Failed: Less than 5 active attendances Researc Communication lessons and/or less than 2 attendances Thesis seminars and/or topic paper not done.

Content scheduling

Basics of academic writing
Theses: Types and relevant agreements
The process of thesis writing ( from thesis topic idea to publication)
Basic skills in thesis writing and thesis reporting
Information search

Further information

The course is online course, the link is in Itslearning.
The course is run in parallel in Finnish and English. In English starts in week 2 and is every other week, in Finnish begins in week 5.

Evaluation scale

Hyväksytty/Hylätty

Assessment criteria, fail (0)

Failed: Less than 5 active attendances Researc Communication lessons and/or less than 2 attendances Thesis seminars and/or topic paper not done.

Assessment criteria, satisfactory (1-2)

N/A

Assessment criteria, good (3-4)

N/A

Assessment criteria, excellent (5)

N/A

Objective

By the end of the course students will have the knowledge to:
• Create a podcast concept
• Understand how to brand a podcast
• Assess and chooses recording equipment
• Script, record, and edit a podcast
• Understand the different distribution channels and assess their strengths and weaknesses
• Know how to market and promote a podcast
• Understand IPR and know where to access royalty free music

Content

Podcast concept and research
Branding
Scripting
Recording
Audio editing
Distribution
Transcription
Marketing
IPR

Materials

Teacher supplied material as required

Teaching methods

Interactive classroom lectures and group work. Students will work in self-assigned groups drawing from research and their own ideas, opinions and experiences.

Exam schedules

There is no exam for this course

International connections

Students will learn the process of podcast creation from initial concept through to recording and editing a finished 20 minute podcast episode. The course will include:
Developing a podcast concept
Creating a brand - including name and logo
Scripting
Transcription - AI as a help
Distribution channels
Recording - equipment, room requirements
Audio editing
Marketing
IPR

Completion alternatives

None

Student workload

Classroom activities: 30 h
Group work: 20 h

Content scheduling

Podcast concepting and research
Researching podcast themes
Researching audiences
Researching niche opportunities
Researching formats - Interviews, music, discussion, reporting?
Researching how using AI can help with the concept

Further information

This course is for anyone with an interest in starting a podcast. It is practical with a strong emphasis on learning by doing. By the end of the course each group will have a fully defined podcast concept, a clear brand outline, a marketing roadmap and one ready to publish podcast episode in the bag. Although the language of instruction is English your podcast can be recorded in your language of preference.

Evaluation scale

H-5

Assessment methods and criteria

Assessment is a combination of teacher observation of student commitment, effort and engagement during lessons together with the standard of 4 completed classroom task based assignments. Students will be assessed on overall communicative competence and language appropriacy within specific communication contexts

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.

Assessment criteria, satisfactory (1-2)

The student has completed the tasks with the minimum of set requirements stated in the task instructions. The student has completed tasks later than the given deadlines. The student has not addressed feedback provided by the teacher.

Assessment criteria, good (3-4)

The student has completed the tasks well fulfilling most of the set requirements stated 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 reflected on their own performance and has been given peer feedback.

Assessment criteria, excellent (5)

The student has completed the tasks very well fulfilling or surpassing the set requirements as stated in the task instructions. The student has completed tasks within the given deadlines or earlier and has addressed feedback provided by the teacher. The student 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://cisco.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

After completing the course the student can:
Describe different project management methods and frameworks and their feasibility to different projects.
Ability to function as a project manager in different phases of a project and produce the project related specifications and documents.
Describe different project management association and certifications.
Risk analysis and quality assurance.

Content

The course covers aspects of different project management methods, such as waterfall and agile as well as different project management associations and certifications. Furthermore, the course covers topics about project management, including project planning, budgeting, scheduling and WBS, risk assessment and quality assurance.

Materials

Various internet sources, links & descriptions online

Teaching methods

Lectures, group work and independent work, project work, online activities

Exam schedules

-

International connections

Practical assignments and reports
Project work
Self study

Completion alternatives

-

Student workload

Lectures and on-site activities: 54 hours
Assignments and self study: 71 hours
Guest lectures + report: 10 hours
TOTAL 135 hours

Content scheduling

The course starts with the course introduction and team building followed by Scrum simulation. The focus is set on agile project management, especially Scrum framework. There after the aspects of waterfall project management methodology are discussed. The student learns how to create a realistic project plan, budget, timeframe and risks for the project. In addition, student learns setting up goals for the project that create customer value, resource allocation and division of work and sizing. IPMA International Project Management Association and other project management institutions and activities are presented as well as IPMA standards – Individual Competence Baseline. Students also practice risk management and risk analysis in more detail. Lastly, quality management in software engineering is handled in lectures and group work.

Further information

Course material is in It´s Learning

Evaluation scale

H-5

Assessment methods and criteria

Assignments and reports: diagnostic assessment.

Course includes 7 assignments: 2 individual assignments and 5 group assignments. Maximum points of each assignment is 3 points. Thus, the maximum amount of points from assignments is 21.

In addition course includes 1 guest lecture report, which is assessed pass/fail.

Team work: formative assessment taking into account student's self and peer assessment.

Presence
50-59% attendance affect on your grade +0,1
60-64% attendance affect on your grade +0,2
65-69% attendance affect on your grade +0,3
70-74% attendance affect on you grade +0,4
75+% attendance affect on your grade +0,5

Final grade of the course is weighted average:
- Assignments 80%
- Presence 10%
- Guest lecture report 10%
- Self- and peer assessment is taken into account

Assessment criteria, fail (0)

Less than 7 points from assignments

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

Assessment criteria, satisfactory (1-2)

Grade 1: 7-9 points from assignments + passing guest lecture report
Grade 2: 10-12 points from assignments + passing guest lecture report

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

Assessment criteria, good (3-4)

Grade 3: 13-15 points from assignments + passing guest lecture report
Grade 4: 16-18 points from assignments + passing guest lecture report

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

Assessment criteria, excellent (5)

Grade 5: 19-21 point from assignments + passing guest lecture report

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

Materials

Materials used in the course:

1. ISO27005 standardi
2. Sutton, David (2021): Information security risk management : a practitioner's guide: https://ebookcentral.proquest.com/lib/turkuamk-ebooks/detail.action?docID=6733537
3. Ilmonen, I. & al. (2022): Johda riskejä: käytännön opas yrityksen riskienhallintaan: https://turkuamk.finna.fi/Record/turkuamk.995697291505970?sid=3091696371
4. https://www.enisa.europa.eu/publications/interoperable-eu-risk-management-framework
5. Enisa Threat Landscape 2023 https://www.enisa.europa.eu/publications/enisa-threat-landscape-2023

And potentially other relevant materials

Teaching methods

Theoretical part through lectures and independent study. Guidance through remote meetings as needed. Practical risk assessment work requires acquiring the target company and maintaining communication with the responsible party. On site meetings for guidance, peer support, sharing experiences, project presentations, and evaluations in the upcoming days

International connections

Active project-based learning and problem-solving

Completion alternatives

-

Student workload

Review of the theory section of the information security risk management course and an extensive risk management project

Content scheduling

Information and Cybersecurity are critical areas in modern organizations, and the importance of risk management has been further emphasized. This practical project-based course in risk management provides students with an opportunity to apply the principles and methods of information and cybersecurity risk management in practice. The course aims to develop students' skills in risk identification, assessment, and management, preparing them for future careers in the field of information and cybersecurity.

Course Content:

Prerequisite for this course is a course in information security risk management, covering the ISO 27005 standard risk management process. Students should have a good understanding of the stages of the information and cybersecurity risk management process, including risk identification, assessment, management, and monitoring. The process and stages are reviewed at the beginning of this course.

The student acquires a small or medium-sized organization for which they will conduct a risk assessment. The student is responsible for contacting the organization's representatives. The work can be done individually or in pairs

Students will apply the ISO 27005 standard, along with other risk management frameworks and best practices, to their selected target organization. They will perform the risk assessment and document the results. At the end of the course, students will compile a final report, including the risk assessment findings and recommendations for the target organization. They will present their findings to the class and possibly to representatives from the chosen organization.

Requirements:

Participation in this course requires prior knowledge of information and cybersecurity risk management. Students must also select a target organization for the risk assessment.

This course offers students a unique opportunity to apply their knowledge of risk management to a real-world project and prepares them for careers in the field of information and cybersecurity.

Timeframe:
Spring 2024. Bi-weekly in-person meetings and bi-weekly online meetings based on separate reservations

Evaluation scale

H-5

Assessment methods and criteria

Review task for the theory section 10%
Implementation, documentation, and feedback from the organization for the risk assessment 90%

Assessment criteria, fail (0)

No risk assessment has been conducted

Assessment criteria, satisfactory (1-2)

A brief risk assessment and satisfactory feedback from the organization.

Assessment criteria, good (3-4)

A fairly comprehensive risk assessment and positive feedback from the organization

Assessment criteria, excellent (5)

A comprehensive risk assessment and excellent feedback from the organization

Objective

After completing the course the student can:
- describe the most important software application types and their typical features
- discuss the selection of a proper solution technology
- define the main concepts of programming such as source code, compiler, variable and data type
- read program code written by someone else
- utilize the most important decision and control structures
- recognize basic object-oriented concepts (class and its members, object, reference, exceptions)
- design and implement simple software applications
- draw a flow chart of the program.

Content

- software application structure
- development environment and tools
- variables and data types
- functions
- decision and control structures
- arrays and lists

Materials

Kaikki oppimateriaali ilmoitetaan ItsLearningissä.

Teaching methods

Opintojaksolla opetellaan uudet asiat ensin opettaja-vetoisesti. Opettaja esittelee teoreettisen taustan. Sen jälkeen opettaja näyttää omalta koneelta ohjelmoiden, miten uusi opiskeltava asia tuodaan ohjelmointitehtäviin. Opiskelijat tekevät saman ohjelmointiharjoituksen omalla koneellaan.

Tämän jälkeen opettaja antaa opiskelijoille harjoitustehtäviä, joissa pääpaino on opiskeltavassa asiassa. Sen jälkeen jatketaan harjoitustehtävillä, joissa uusi asia integroidaan jo opittuihin asioihin. Kun opiskelijat tekevät harjoitustehtäviä, molemmat opettajat ovat opiskelijoiden tukena.

Exam schedules

Opintojaksolla ei ole tenttiä.

International connections

Opintojaksolla opetellaan uudet asiat ensin opettaja-vetoisesti. Opettaja esittelee teoreettisen taustan. Sen jälkeen opettaja näyttää omalta koneelta ohjelmoiden, miten uusi opiskeltava asia tuodaan ohjelmointitehtäviin. Opiskelijat tekevät saman ohjelmointiharjoituksen omalla koneellaan.

Tämän jälkeen opettaja antaa opiskelijoille harjoitustehtäviä, joissa pääpaino on opiskeltavassa asiassa. Sen jälkeen jatketaan harjoitustehtävillä, joissa uusi asia integroidaan jo opittuihin asioihin. Kun opiskelijat tekevät harjoitustehtäviä, molemmat opettajat ovat opiskelijoiden tukena.

Completion alternatives

1) Antamalla näytön esim. tekemästään työelämän projektista, jolla opiskelija osoittaa hallitsevansa opintojakson sisällön.
2) Sivustolla mooc.fi kuvataan ohjelmoinnin MOOC, joka vastaa sisällöltään Helsingin yliopiston tietojenkäsittelytieteen laitoksen kursseja Ohjelmoinnin perusteet ja Ohjelmoinnin jatkokurssi. Kurssit vastaavat yhteensä kymmentä opintopistettä (5+5).
Ohjelmoinnin perusteet voi suorittaa tekemällä ohjelmoinnin MOOCin alkuosan.

Student workload

Opiskelijan työn mitoitus

5 opintopistettä: 27 * 5 = 135 tuntia

Opintojakson kesto: 8.1. - 19.4.2024 (14 viikkoa + opetukseton viikko 8)

Viikkotyömäärä: 135 tuntia / 14 viikkoa = 9,5 tuntia viikossa

Content scheduling

Opintojaksolla opiskellaan ohjelmoinnin ajattelutapaa sekä tutustutaan ohjelmistokehityksen pääpiirteisiin.

Opintojakson harjoitukset tehdään Javalla.

Tulostaminen näytölle ja tiedostoon.
Tiedon lukeminen näppäimistöltä ja tiedostosta.
Ohjelmoinnin valintarakenteet.
Ohjelmoinnin toistorakenteet.
Aliohjelmat ja niiden käyttö.
Poikkeukset.
Taulukot ja merkkijonot.
Ohjelman dokumentointi.
Ohjelman testaus.

Further information

Kurssin viestintä tapahtuu pääsääntöisesti ItsLearningissä.

Evaluation scale

H-5

Assessment methods and criteria

Opintojakson läpäisy edellyttää hyväksytysti suoritettujen harjoitusten tekemistä sekä aktiivista osallistumista harjoitustyön tekoon.

Viikkokohtaisia kotitehtäviä on 10 sarjaa, kussakin 10 pisteen edestä tehtäviä. Kotitehtäväsarjan kokonaisarviointi noudattaa seuraavaa kaavaa:
40 pistettä -> 1
55 pistettä -> 2
70 pistettä -> 3
80 pistettä -> 4
90 pistettä -> 5

Harjoitustyö arvioidaan erikseen skaalalla 1-5.

Opiskelijan opintojakson arvosana muodostuu kotitehtäväsarjan ja harjoitustyön keskiarvosta. Molempien osioiden pitää olla hyväksyttyjä.

Assessment criteria, fail (0)

Hyväksytysti suoritettuja harjoituksia puuttuu ja/tai harjoitustyö puuttuu.

Assessment criteria, satisfactory (1-2)

Hyväksytysti suoritettuja harjoituksia on tehty minimimäärä tai niiden laatu on tyydyttävä ja/tai harjoitustyön laatu on tyydyttävää tasoa.

Assessment criteria, good (3-4)

Hyväksytysti suoritettuja harjoituksia on tehty riittävästi ja niiden laatu on hyvää ja harjoitustyön laatu on hyvää tasoa.

Assessment criteria, excellent (5)

Hyväksytysti suoritettuja harjoituksia on tehty maksimimäärä ja niiden laatu on kiitettävää ja harjoitustyön laatu on kiitettävää tasoa.

Qualifications

Basic computer skills and high school or vocational school mathematics curriculum or equivalent skills.

Objective

After completing the course the student is able to:
- describebasic tasks and concepts of operating systems
- install and configure an operating system for desktop and server
- act as operating systems administrator

Content

- Operating system tasks and concepts
- Installing and configuring operating system for desktops and servers
- System administrating using command line interface
- User access management
- Server installation and management

Materials

I . Kurssikirjat:

The Linux Command Line: A Complete Introduction
William Shotts
2nd edition
2019
Tästä on olemassa netissä vielä uudempi, päivitetty painos: https://linuxcommand.org/tlcl.php

Mastering Ubuntu Server
Jay LaCroix
4th edition
2022

Kurssikirjoja luetaan vain valikoiduin osin.

Kurssikirjat ovat luettavissa oppilaitoksemme eBook Central -palvelussa.

II. Teoreaosuuden tutoriaali

Operating System Tutorial: https://www.tutorialspoint.com/operating_system/index.htm

III. Opettajan laatimat harjoitustehtävät.

Exam schedules

Kurssin puolen välin jälkeen monivalintatentti käyttöjärjestelmien teoriasta.

Uusintamahdollisuus kurssin päätteeksi.

International connections

Käytännön työskentely luokassa opettajan johdolla
Pääosin kotona tehtävät käytännön harjoitustehtävät
Käyttöjärjestelmien teoria: esitelmän pitäminen ryhmässä
Materiaalin lukeminen
Tenttiminen

Student workload

Käytännön opetusta paikan päällä 24h
Teoriaa paikan päällä sisältäen esitelmän ryhmässä10h
Tentti ja sen uusintatilaisuus 4 h
Oman virtuaaliympäristön valmistelua ja ylläpitoä 7h
Materiaalin läpikäyntiä ja harjoitustehtävien tekemistä 70h
Tenttiin valmistautumista 20h

Content scheduling

Käytännön opetus etenee pääpiirteissään seuraavassa järjestyksessä:

Linux-käyttöjärjestelmän asentaminen virtuaalikuvakkeelle
Johdatus käyttöjärjestelmiin
Bash-komentotulkin peruskäyttö
Pääkäyttäjänä toimiminen
Ohjelmistojen ja prosessien hallinta
Käyttäjien ja oikeuksien hallinta
Bash-komentotulkin kehittyneempi käyttö
Verkkoyhteyksien hallinta
Johdatus palvelimiin
Tietokantapalvelimen asentaminen
Web-palvelimen asentaminen ja hallitseminen
Tietoturvan perusteita

Teoriaopetus etenee pääpiirteissään seuraavasti

Harjoitustyö: esitelmä ryhmässä teoria-aiheesta
Muiden esitelmien seurantaa ja teoriaan perehtymistä tutoriaalin perusteella
Teoriatentti ja sen uusinta.

Evaluation scale

H-5

Assessment methods and criteria

Käytännön osuuden arvosteluskaala (harjoitustehtävät): vähintään 30 pistettä -> 0,5 arvosanayksikköä; 38 pistettä -> 1,0; 46 pistettä -> 1,5; 54 pistettä -> 2,0; 62 pistettä -> 2,5; 70 pistettä -> 3,0. Maksimipistemäärä 80. (Alin hyväksytty suoritus 0,5 arvosanayksikköä)

Harjoitustehtävät tarkistetaan demoiksi ilmoitetuilla luennoilla. Niillä on oltava läsnä. Poissaolosta seuraa 25 prosentin pistevähennys.

Teoriaosuus: harjoitustyö ryhmässä 10 pistettä ja tentti 20 pistettä.

Teoriaosuuden arvosteluskaala: vähintään 12 pistettä -> 0,5 arvosanayksikköä; 16 pistettä -> 1,0; 20 pistettä -> 1,5; 24 pistettä -> 2,0. Maksimipistemäärä 30. 0,0-2,0 (Alin hyväksytty suoritus 0,5 arvosanayksikköä)

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
Internet material about SQL and noSQL

Teaching methods

The course consists of 1) exercises (db queries and design tasks) 2) practical work tasks and 3) exam. Exercises are divided into weekly topics. These are practiced both individually and with the help of the teacher in the session. Each session begins with an introduction to the topic of the week, which includes practical examples with lecture slides.

Exam schedules

The exam is performed in Ville system.
1st exam is organized in the class room (during the regular meeting time) where Internet use is allowed for information retrieval. 2nd and 3rd exams as e-exams in the aquarium premises where Internet use is not allowed. E-exams are open the rest of the year.

International connections

Learning by doing, trial-error, listening carefully the teacher, and collaborating with other students, self- and peer-assessments.

Completion alternatives

Participation in the teaching session is not compulsory, but highly recommended. Each week we introduce a new topic that builds on top of previous weeks.

Remote self-studying in online mode is possible (with slightly different emphasis in topics and grading, announced in the beginning of the course).

Student workload

Recommended 8 hours / week for lectures, solving exercises and practical work tasks, if you are new to relational databases.

Participating weekly in teaching sessions: a' 3 hours * 14 =42h
Individual work:
for exercises 50h
Practical work 30h
Exam 10h

Content scheduling

In this course, students learn to use and design relational databases as well as understand differences to document databases.
Weekly meetings.Topics (and hours used in teaching sessions):
- Relational DBMS and DB use 4h
- Basics of SQL 13h
- Relational database design 7h
- Introduction to document database MongoDB 4h

Further information

We will use a DBMS environment for practical training (MySQL), which needs installation on the personal computer.
Highly likely, the environment for using DBMS is some LAMP stack with graphical UI like UwAmp, but you can use similar like XAMPP.
In addition to DBMS environment, we will use MongoDB cloud for practicing document databases.

Evaluation scale

H-5

Assessment methods and criteria

The course is graded from 0-5. The grade is based on collected points.
Each exercise is 1 point unless mentioned otherwise. The exam must be passed.

Exercises: 65 points,
Practical work: 55 points
Exam 70 points;
Total 190 points

Grading by points:
Points Grade
0-89 NOT PASSED
90-107 1
108-124 2
125-144 3
145-159 4
160-190 5

Objective

After completing the course the student is able to:
- Work as a member of a project team and describe how ICT projects are managed.
- Document and report project results.
- Utilize different environments and platforms for learning.
- Use the techniques available when creating internet pages, and create working www-page using them.
- Use Information Technology tools when working in project.
- Describe what specialization options are available in Business IT program.
- Be familiar with the ICT degree programme's competence tracks' contents, applications and business cooperation.
- Analyze one’s own competences, interests, strengths and development areas.

Content

Introduction to Project Management.
Introduction to Version Control.
Practical project work.
Getting familiar with competence tracks' contents, laboratories, and projects.
Career planning and choosing one's preference for competence track.

Evaluation scale

H-5

Objective

After completing the course the student can:
- list regulations of data protection in Finland and in EU
- give examples of the duties of personnel working with data protection and privacy
- construct a privacy policy
- protect his/her privacy in electronic data communication
- provide examples of the rights to check how his/her own privacy has been protected in different environments
- plan and conduct actions required by the data and privacy protection in an SME sector enterprise or similar size organization
- assess the efficiency of these actions and give justified improvement proposals for them

Content

The course contains knowledge of the following areas:
- General Data Protection Regulation
- Practical Data Protection
- Online Privacy

Materials

Oppimateriaali ja tehtävät ovat Itslearningissä.

Exam schedules

Kurssin puolivälissä.

International connections

Luennot, henkilökohtaiset tehtävät, ryhmätyö, tentti.

Student workload

Ryhmätyö käytännön tietosuojakysymyksistä. Pakollinen läsnäolo töiden esittelyissä.
Luennot: 26h
Henkilökohtaiset tehtävät ja ryhmätyö: 80h
Koe (sisältäen valmistautumisen): 29h

Content scheduling

Tietosuojan säännökset Suomessa, EU:ssa ja maailmalla.
Tietosuojavaltuutetun toiminta ja tehtävät.
Tietosuojavastaavan toiminta ja tehtävät.
Tiedon suojaaminen tietoliikenteessä.
Yksityisyyden turvaaminen lainsäädännössä.
Työelämän tietosuoja.
Tiedon suojaaminen sosiaalisessa mediassa ja internetissä.

Further information

Kurssi ja sen viestintä on Itslearningissä.

Evaluation scale

H-5

Assessment methods and criteria

Henkilökohtaiset tehtävät, ryhmätyö, tentti. Jokaisesta osasta on saatava hyväksytty arvosana.

Assessment criteria, fail (0)

Hylätty arvosana henkilökohtaisista tehtävistä, ryhmätyöstä tai tentistä.

Assessment criteria, satisfactory (1-2)

40%-55% henkilökohtaisista tehtävistä palautettu hyväksytysti.
40%-55% hyväksytty suoritus ryhmätyöstä.
Alle 15/25 pistettä tentistä.

Opiskelijalla on perusymmärrys tietosuojan sääntelystä ja tietää mistä löytää lisätietoja. Opiskelija tunnistaa tiedon suojaamisen teknisiä ratkaisuja.

Assessment criteria, good (3-4)

55%-85% henkilökohtaisista tehtävistä palautettu hyväksytysti.
55%-85% hyväksytty suoritus ryhmätyöstä.
Alle 20/25 pistettä tentistä.

Opiskelija tuntee tietosuojan sääntelyä sekä tuntee päätoimijoiden tehtävät ja vastuut. Opiskelija osaa suositella sopivia teknisiä ratkaisuja tiedon suojaamiseen sekä tietää miten toimitaan tietomurron sattuessa.

Assessment criteria, excellent (5)

>85% henkilökohtaisista tehtävistä palautettu hyväksytysti.
>85% hyväksytty suoritus ryhmätyöstä.
Yli 20/25 pistettä tentistä.

Opiskelija tuntee tietosuojan sääntelyä sekä tuntee päätoimijoiden tehtävät ja vastuut, minkä lisäksi ymmärtää edellytykset tiedon käsittelylle ja siirrolle. Opiskelija osaa suositella sopivia teknisiä ja hallinnollisia ratkaisuja tiedon suojaamiseen sekä toimia itsenäisesti tietomurron sattuessa. Opiskelija osaa arvioida tietosuojaa.

Objective

After completing the course the student will be able to:
- Understand organizational functions and main business processes
- Describe business processes and process management principles
- Understand basic concepts of business operations and calculate key figures
- Identify different information management needs in business

Content

- Business plan
- Material-, information- and financial processes
- Business process management
- Business development

Materials

Materials created by the teacher, as well as an optional book/reading package.

Teaching methods

f2f training sessions, group work, personal reading, examination

Exam schedules

During the course, an exam will be held based on the lectures and other shared materials.

International connections

The course aims to introduce the student to the fundamentals of business through business development. Work involves developing a business idea, company, and its operations from both a strategic and operational perspective. Business development is done in small groups, and the output is presented, discussed, and evaluated in the form of a business plan. Students can tailor their own learning goals by choosing a business-related book or reading material of their interest. The exam aims to support the understanding of fundamental business concepts.

Student workload

Face-to-face instruction: 42 hours
Group work: 50 hours
Personal reading package: 30 hours
Exam: 10 hours

Content scheduling

weekly face-to-face training is delivered as introductory sessions and workshop work in small groups. Topics covered include, among others, product, customer segments, marketing communication, customer relationship management, data and goods flows, the concept of quality, business models, finance, and related concepts.

Evaluation scale

H-5

Assessment methods and criteria

The course grade is determined with the following weights:
50% for group work on business development presentations and final report (business plan)
25% for personal reading package
25% for personal exam

Group work requires personal initiative from the student, and peer feedback can be utilized in the assessment.

Assessment criteria, satisfactory (1-2)

The student uses key business terms and basic theories to report findings and observations. Can describe, classify, and list things. The output is descriptive but lacks reflection or insights. The student participates in group discussions.

Considerable guidance and support have been needed for the group's business idea planning. Collaboration within the group does not work or is difficult. Feedback has not been effectively utilized within the group. There are inconsistencies in the business plan, and it does not support the sale of the idea as desired. The course material and other sources have been used sparingly. The course concepts presented have not been applied in the plan. The plan is only partially feasible.

Assessment criteria, good (3-4)

The student understands the bigger picture and uses theory to describe it. Shows the ability to apply a principle related to the topic and can combine ideas. Utilizes acquired material in their own and group work. Participates in group discussions, is active in creating the business plan, and takes responsibility for group tasks.

The group's business idea is quite creative. It has been planned independently and in consensus with the entire group. The business plan is a clear and consistent document. The application of course concepts to their own business plan demonstrates expertise. The plan is largely feasible. The presentation is clear, understandable, and persuasive.

Assessment criteria, excellent (5)

The student identifies critical success factors for the industry and company, understands theory, and presents their findings with justification. Can identify areas for improvement and is a critical thinker. Can analyze cause-and-effect relationships and handle issues insightfully. High-quality background material has been independently sought and found, and its use is justified. The student actively, proactively, and responsibly participates in group discussions and takes the group's knowledge to a deeper level.

The group's business idea is innovative and creative. It has been planned enthusiastically, responsibly, and in consensus with the entire group. Various sources and course materials have been used extensively. The business plan and presentation are clear, understandable, consistent, persuasive, and creative. The plan is for most parts feasible.

Objective

After having completed the course, the student:
• can describe different topical areas of ICT, their interfaces to other fields and application opportunities from different perspectives
• can identify channels to contribute to the development of the society in general and own professional field in particular
• is familiar with the ICT degree programme's competence tracks' contents, applications and business cooperation
• analyze one’s own competences, interests, strengths and development areas

Content

* getting familiar with competence tracks' contents, laboratories, and projects
* career planning and choosing one's preference for competence track

Materials

Itslearning

Teaching methods

Lectures, practical work, reports etc.

Exam schedules

Taking the course requires attendance and finishing the given tasks. The is no chance for a retake after the course has ended.

International connections

Attendance & assignment requirements for each part are specified in Itslearning.
DEAI - Data Engineering and Artificial Intelligence
DNCS - Data Networks and Cybersecurity
EMB - Embedded Software and IoT
GAME - Game and Interactive Technologies
SEPM - Software Engineering and Project Management
EHEA - Health Technology

Completion alternatives

None

Student workload

Two weekly morning sessions per each part plus tasks / exercises.

Assessment criteria, approved/failed

To pass the course, students must pass 5/6 of the parts.

Content scheduling

The course consists of six parts, one for each competence track.
Lessons in Jan - April 2024, timetables for each group available in lukkari.turkuamk.fi.

Further information

Itslearning

Evaluation scale

Hyväksytty/Hylätty

Objective

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

· Configure VLANs and Inter-VLAN routing applying security best practices.
· Troubleshoot inter-VLAN routing on Layer 3 devices.
· Configure redundancy on a switched network using STP and EtherChannel.
· Troubleshoot EtherChannel on switched networks.
· Explain how to support available and reliable networks using dynamic addressing and first-hop redundancy protocols.
· Configure dynamic address allocation in IPv6 networks.
· Configure WLANs using a WLC and L2 security best practices.
· Configure switch security to mitigate LAN attacks.
· Configure IPv4 and IPv6 static routing on routers.

Content

CCNAv7: Switching, Routing, and Wireless Essentials (SRWE) covers the architecture, components, and operations of routers and switches in small networks and introduces wireless local area networks (WLAN) and security concepts. Students learn how to configure and troubleshoot routers and switches for advanced functionality using security best practices and resolve common issues with protocols in both IPv4 and IPv6 networks. 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://cisco.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 covers the architecture, components, and operations of routers and switches in small networks and introduces wireless local area networks (WLAN) and security concepts. Students learn how to configure and troubleshoot routers and switches for advanced functionality using security best practices and resolve common issues with protocols in both IPv4 and IPv6 networks. The course includes activities using Packet Tracer, hands-on lab work, and a wide array of assessment types and tools. By the end of the course, students will be able to:

- Configure VLANs and Inter-VLAN routing applying security best practices.
- Troubleshoot inter-VLAN routing on Layer 3 devices.
- Configure redundancy on a switched network using STP and EtherChannel.
- Troubleshoot EtherChannel on switched networks.
- Explain how to support available and reliable networks using dynamic addressing and first-hop redundancy protocols.
- Configure dynamic address allocation in IPv6 networks.
- Configure WLANs using a WLC and L2 security best practices.
- Configure switch security to mitigate LAN attacks.
- Configure IPv4 and IPv6 static routing on routers.

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 (TE00BU11) or equivalent skills.

Objective

Deepening knowledge of 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

International connections

Practical assignments and reports
Project work
Self study

Completion alternatives

-

Student workload

Lectures and on-site activities: 86 hours
Assignments and self study: 66 hours
Project work 108 hours
Guest lectures + report: 10 hours
TOTAL 270 hours

Content scheduling

This course deepens project working skills on ICT field as well as substance knowledge of different ICT field -related topics. 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

Course material is in It´s Learning

Evaluation scale

H-5

Assessment methods and criteria

Course includes 6 assignments: 2 individual assignments and 4 group assignments. Maximum points of each assignment is 3 points. Thus, the maximum amount of points from assignments is 18.

In addition course includes 1 guest lecture report, which is assessed pass/fail.

Team work: formative assessment taking into account student's self and peer assessment.

Presence
50-59% attendance affect on your grade +0,1
60-64% attendance affect on your grade +0,2
65-69% attendance affect on your grade +0,3
70-74% attendance affect on you grade +0,4
75+% attendance affect on your grade +0,5

Final grade of the course is weighted average:
- Group assignments inc. self and peer assessment 40%
- Presence 10%
- Guest lecture report 10%
- Project work inc- self and peer assessment 40%

Assessment criteria, fail (0)

Less than 6 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: 6-7 points from assignments + passing guest lecture report + completing project work hours
Grade 2: 8-10 points from assignments + passing guest lecture report + 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: 11-13 points from assignments + passing guest lecture report + completing project work hours
Grade 4: 14-16 points from assignments + passing guest lecture report + 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: 17-18 point from assignments + passing guest lecture report + 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.

Objective

After completing the course the student can:
Act as a sales person in demanding technical sales.
Sell complicated technical solutions.
Lead sales project.

Materials

Internet sources, links & descriptions online

Teaching methods

Lectures, team work, independent work and online activities

Exam schedules

No exam

International connections

Practical assignments and reports
Team work
Self study

Completion alternatives

No optional ways for implementation

Student workload

Lectures and on-site activities: 72 h
Assignments and self study 63 h
TOTAL 135 hours

Content scheduling

The course starts with different aspects of tehnical sales. The student learns how to match technology and business, understand the customer needs and busines cases. There after different kinds of marketing and sales strategies and processes are presented as well as offers and contracts. After that, the focus is set on account management. Last, business ethics is handled in lectures and team work.

After the course students have a clear understanding of technical sales as part of the work of the future.

Further information

Course material and assignments are in It´s Learning

Evaluation scale

H-5

Assessment methods and criteria

Assignments and reports: diagnostic assessment.

Course includes 6 assignments: 2 individual assignments and 4 group assignments. Maximum points of each assignment is 3 points. Thus, the maximum amount of points from individual assignments is 6 points and 12 points from group assignments.

Team work: formative assessment taking into account student's self and peer assessment.

Presence
50-59% attendance affect on your grade +0,1
60-64% attendance affect on your grade +0,2
65-69% attendance affect on your grade +0,3
70-74% attendance affect on you grade +0,4
75+% attendance affect on your grade +0,5

Final grade of the course is weighted average:
- Individual assignments inc. self assessment 30%
- Group assignments inc. self and peer assessment 60%
- Presence 10%

Assessment criteria, fail (0)

Less than 4 points from group assignments
Less than 2 points from individual assignments

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

Assessment criteria, satisfactory (1-2)

Grade 1:
- 4 points from group assignments
- 2 points from individual assignments

Grade 2:
- 5-6 points from group assignments
- 3 points from individual assignments

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

Assessment criteria, good (3-4)

Grade 3:
- 7-8 points from group assignments
- 4 points from individual assignments

Grade 4:
- 9-10 points from group assignments
- 5 points from individual assignments

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

Assessment criteria, excellent (5)

Grade 5:
- 11-12 points from group assignments
- 6 points from group assignments

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

Qualifications

Technical solution selling.
Project selling.
Special issues in selling complicated technical solutions.

Objective

After completing the course the student can:
- describe different software development methodologies and evaluate their feasibility to software projects

- describe software development project phases

- understand and draw UML diagrams

- understand the importance of specification and planning to software development

- work in different phases of a software project

Content

- Software development project

- Specification, planning, programming, testing, deployment, and maintenance of a software project

- UML modelling

Materials

Erikseen jaettavat ja linkatut lähiopetuskertojen materiaalit, ohjelmistotyökalut, dokumentointipohjat.

Teaching methods

Opintojaksolla harjoitellaan toimimista ohjelmistoprojektin eri vaiheissa.
Harjoitustyönä toteutetaan ryhmässä hallittu ohjelmistoprojekti alusta loppuun: Ohjelmiston määrittely, suunnittelu, ohjelmointi, testaus, ja käyttöönotto.

International connections

Harjoitustyö toteutetaan ryhmässä. Projektissa noudatetaan SCRUM menetelmän periaatteita. Viikoittaisilla opetuskerroilla tehdään ohjelmistuotantoon liittyviä pienempiä tehtäviä, jotka palvelevat harjoitustyön tekemisen osia sekä edistetään omaa harjoitustyöprojektia.

Student workload

Opintojakson laajuus on 5 opintopistettä.
Työmäärä on 5 * 27 tuntia eli 135 tuntia.
Opintojakson kesto on noin 14 viikkoa.
Viikottainen työmäärä on noin 10 tuntia, josta
viikkoharjoitukset noin 2 tuntia ja oma harjoitustyönä oleva
ohjelmistoprojekti noin 8 tuntia.

Content scheduling

Opintojakson suoritettuaan opiskelija :
- tuntee ohjelmistoprojektimalleja ja arvioida niiden soveltuvuutta ohjelmistoprojekteihin
- osaa toimia ohjelmistoprojektin eri vaiheissa ja rooleissa
- ymmärtää määrittelyn, suunnittelun ja testauksen merkityksen ohjelmistoprojektissa
- osaa laatia ohjelmistotuotannossa käytettyjä suunnittelukaavioita (UML), käyttöliittymäprototyyppejä ja käyttää versionhallintaa yhteistyössä muiden kanssa
- käyttää ketterää kehitystä tukevaa työkalua ohjelmistoprojektin ja vaatimustenhallintaan

Further information

Osallistumisen edellytyksenä ovat perustaidot jostakin ohjelmointikielestä. Kurssilla toteutetaan ryhmätyönä ohjelmisto, mutta ohjelmoinnin opetus ei ole varsinaisesti kurssin sisältöä.

Evaluation scale

H-5

Assessment methods and criteria

Harjoitustyö muodostaa 60 % arvosanasta. Opintojaksosta läpipääsy edellyttää hyväksytysti suoritettua harjoitustyötä
Aktiivinen osallistuminen lähiopetukseen muodostaa 40 % arvosanasta
Harjoitustyön välipalautukset (sprinttien tuotokset) arvostellaan pistein 0-2, jossa:
2 pistettä: Erittäin hyvä (tehtävät palautettu ajoissa, tehty tehtävänannon mukaisesti, ei puutteita)
1 piste: Hyväksytty (tehtävät palautettu ajoissa, tehty tehtävänannon mukaisesti, pienehköjä puutteita)
0 pistettä: Hylätty (tehtäviä ei palautettu ollenkaan, osa tehtävistä puuttuu, tehtävät palautettu myöhässä tai tehtävät ovat erittäin puutteellisia)
Lähiopetukseen osallistumisesta saa 1 pisteen / kerta. Pisteen saaminen edellyttää aktiivista osallistumista ja tehtävien tekemistä lähiopetustunteihin liittyen. Niinä kertoina, kun erillistä oppituntitehtävää ei ole, pisteen saa läsnäolosta. Läsnäolot kerätään joka oppitunnilla, mutta ainoastaan tehtävittöminä oppituntikertoina niistä saa suoraan pisteen.
Kurssin arvosana muodostuu seuraavasti:
Harjoitustyön pistemäärä = arvosana: 0-5p. = 0, 6-8p. = 1, 9-10p. = 2, 11-12p. = 3
Lähiopetuksen pistemäärä = arvosana lisäys: 0-6p. = +0; 7-10p. = +1; 11p. tai enemmän = +2 harjoitustyön arvosanaan. Jos jostain syystä yhteenlasketut maksimipistemäärät poikkeavat yllä olevista, kertyneet pisteet skaalataan yllä ilmoitetulle välille lineaarisesti.

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

Mainly according to the book (from chapters 1-10)
[Aurélien Géron] Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, Publisher : O'Reilly Media; 2022, 3rd Edition

In addition: Material prepared by the teacher, online material and tasks in the learning environment.

International connections

The course includes approximately 12 guided working and theory sessions, 9 personal practice tasks and group work.
*
Group work is done in groups of 3-4 people outside of guidance sessions. The group sets aside 15 minutes outside of guidance sessions to present the group work.

Student workload

Contact hours:
- Course start-up: 2h
- Weeks 3 - 5: Theory & practice (3h/week): 5 x 3h = 15h
- Weeks 9 - 15: Theory & practice (3h/week): 7 x 3h = 21h
- Week 16: Project work presentations: 3h
- In addition, in weeks 4 - 15, about 10 support and inquiry hours: 10 x 1h = 10h

Total contact hours: about 51 hours

Independent study and homework: about 90 h

Content scheduling

Week 2:
- Machine learning landscape (Introduction to machine learning)
Weeks 3 - 7:
- End-to-end machine learning process
Weeks 9-15:
- Presentation of teamwork
- Classification
- Training linear models
- Decision trees
- Unsupervised learning
- Neural networks (Introduction to neural networks)
Week 16: Presentation of project works

Further information

The course materials and assignments are at ITS.
The exercises are mainly performed using Jupyter Notebook.
Communication about the course via ITS, but also via the course's Teams channel.

Evaluation scale

H-5

Assessment methods and criteria

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

You get points from the exercises n the contact class and homework, which affect the evaluation by 3 units.
About half of the exercises are done in contact classes.

The project work also affects the evaluation by 2 units. The project work is graded in ITS from 0 to 5, which is influenced by both the teacher's assessment and the peer assessment given by the rest of the project team.

The course can only be passed by doing both practice tasks and participating in project work.

Assessment criteria, fail (0)

The student does NOT participate in the project work or gets the project work grade 0 (Failed) OR did not get at least 40% 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 60-84% of the points for the exercises in the course AND got a grade of 3 - 4 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:
masters JavaScript and can use some of the most important libraries in developing browser user interfaces
can implement dynamic and responsive browser user interfaces that are usable in variety of devices
masters AJAX technology and JSON data-interchange format
can use efficient tools in browser scripting

Content

JavaScript
jQuery
Doing asynchronous requests with AJAX
JSON data-interchange format
Tools for developing browser interfaces
Implementing a small scale dynamic and responsive browser user interface

Materials

The course books (Selected parts)
*
Eloquent JavaScript
Marijn Haverbeke
No Starch Press; 3 edition (December 4, 2018)
Available on the Net: http://eloquentjavascript.net
*
Professional JavaScript for Web Developers
5th Edition
Matt Frisbie
Published by Wrox
Available in ProQuest EBook Central
*
Learning React : Modern Patterns for Developing React Apps
2nd edition
Alex Banks and Eve Porcello
Available in ProQuest EBook Central
*
Only selected chapters will be read.

Content scheduling

Contents

I. JavaScript (Lectures and personal exercises)

- Basics
- Strings
- Objects, destructuring
- Arrays, array operations
- Programming functions
- Error handling
- DOM, event handling
- Modules
- Asynchronous programming
- Tools

II. React (Lectures and a teamwork)

- Basics
- JSX
- Components
- Modularization
- Tools
- Managing state
- Hooks

III. Teamwork: A simple single page web application with React (without backend)

7 personal JavaScript exercises.
React-based Teamwork.

Evaluation scale

H-5

Assessment methods and criteria

7 personal assignments: 70 points
The group project work: 30 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.

The student must get at least 30 points from the assignments and 10 points from the group work to pass the course.

The grading scale (points b -> grade):

40 points -> 1
55 points -> 2
70 points -> 3
80 points -> 4
90 points -> 5

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 sessions when 3 hours for theory and practical exercises.
Additionally, weekly 1h sessions for questions and support in exercises.

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

-

Student workload

Contact hours
- Course introduction: 3 hours
- 12 times 3h theory and practice: 12 x 3h = 36 hours
- 10 times Questions & Support: 10 x 1h = 10 hours

Home work:
- Working with assignments: approximately 80 hours

Total: approximately 130 hours

Content scheduling

Week 2: Course introduction

Weeks 2 - 15
- 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 points from practical exercises in class room and home work exercises.
Around half of the exercises are done during the contact hours.

Additionally, there is an exam during the last contact session that will be used an option to pass the course with grade 1 or 2.

Assessment criteria, fail (0)

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

Assessment criteria, satisfactory (1-2)

50% - 69% points in the exercises OR student has passed the test in the final contact session.

Assessment criteria, good (3-4)

70% - 89% points in the exercises.

Assessment criteria, excellent (5)

At least 90% points in the exercises.

Qualifications

Introduction to Programming, or equivalent programming skills

Objective

After completing the course the student can:
- describe basic solutions for data architectures and big data
- select and use suitable data architecture
- apply ETL process and tools for handling of big data

Content

Architecture and Components of Big Data Frameworks
ETL process with Big Data for batch and streaming
Practical work with suitable tools and frameworks

Materials

Teacher provided lecture material
Supporting public online material
Teacher provided virtual machines
All needed material (or at least a link to them) will be available in itslearning.

Teaching methods

Contact learning, practical exercises, independent study

International connections

Given examples and exercises support each topic studied during the lectures. Additional material in the form of tutorials and reliable information sources is provided.

Student workload

Contact hours 56 h
Inpendent studying 79h, including:
- Studying the course material
- Completing exercises
- Project

Content scheduling

-The basic idea of data engineering methods and pipelines
-different components
-integration of said components (MQ systems)
-data engineering frameworks (Apache family)
-The goal of the course is to be able to build a data pipeline from start to finish

Further information

Itslearning and contact classes are the main communication channels used on this course.

The student is required to have a computer capable of running a simple Ubuntu virtual machine.

Evaluation scale

H-5

Assessment methods and criteria

Homework exercises returned throughout the course
Small project at the end of the course

Objective

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

Content

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.

Exam schedules

No Exam.

International connections

The course includes approximately 13 guided working and theory sessions, 9 personal practice tasks and a group work final project.
*
Final project is done in groups of 3-4 people outside of guidance sessions. The group sets aside 15 minutes to present the group work during the last session.

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 70 hours

Total: approximately: 135 hours

Content scheduling

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


We proceed in general according to the chapters in the course book.

Further information

Qualifications:

- Python programming skills and skills in utilizing Pandas for data manipulation and Numpy for numerical operations and array handling are required.
- Basic knowledge of probability, statistics and linear algebra is also beneficial.

Evaluation scale

H-5

Assessment methods and criteria

- The course is graded on a scale of 0-5.
- In order to receive an approved performance, the student must receive an acceptable mark for both 1) personal practice tasks (exercises) and 2) teamwork project.
- You get points from the 9 homework exercises, which affect the evaluation by 3 units.
- Occasionally, there may be classwork exercises, but their points are mostly optional and are considered as bonuses.
- The project work also affects the evaluation by 2 units. The project work is graded in ITS from 0 to 5, which is influenced by both the teacher's assessment and the peer assessment given by the rest of the project team.
- The course can only be passed by doing both personal practice tasks and participating in teamwork project.

Assessment criteria, fail (0)

The student does NOT participate in the project work or gets the project work grade 0 (Failed) OR did not get at least 40% 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 60-84% of the points for the exercises in the course AND got a grade of 3 - 4 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.

Evaluation scale

H-5

Objective

After completing the course, the student can:

Describe what artifical intelligence (AI) is about and how to build solutions that utilise artificial intelligence.

Content

Basics of AI
Recap of Machine Learning
Examples of solutions utilizing AI

Evaluation scale

H-5

Objective

After completing the course, the student can:

Describe what DevOps is and how it relates to software engineering,
Use tools and environments needed for DevOps,
Use DevOps in a software project.

Content

Basics of software production
DevOps model
Tools and Environments for DevOps
DevOps in practice
Project work

Evaluation scale

H-5

Objective

After completing the course the student can:
- explain the different phases and main methods of the development of a software product
- explain the concepts class hierarchy, inheritance, and polymorphism, and utilize these in software development
- discuss the possibilities of parallel programming
- apply exception handling mechanisms
- design, implement and document a simple user interface application.

Content

- object-oriented structures
- error handling with exceptions
- threads
- database connection
- software development process and methods
- UML diagrams

Materials

All the learning materials are mentioned in ItsLearning

Teaching methods

The course is structured as separate lectures and demo sessions. During the lectures, the teacher will go through the theory and the students are coding some exercises together with the teacher using their own computers.

Reading the given material and coding the programming exercises and exercise work.

Demonstrating and documenting the exercises and exercise work.

Exam schedules

There is no exam in this course

International connections

Self assessment
Student regularly pays attention to own learning and studying.
Students are asked to take notes from each programming exercise and contemplate at least the following:
* Topic area: What did I know about the topic beforehand? What did I think about the area?
* While coding: Thoughts about the challenge level and interest of the exercise.
* Afterwards: What did I learn?

Moreover, students learn to assess their own work regarding every assignment using scale: Excellent - Good - Sufficient.

Completion alternatives

1) Demonstrate e.g. a real work life project and showing that student masters the contents of this course.

2) mooc.fi contains a programming MOOC, whose contents covers the Introduction to Programming and Advanced Programming courses of the University of Helsinki. Courses are 10 credits together (5+5). Object oriented course can be alternatively completed by completing the second part of the course (i.e., parts 8 to 14).

Student workload

To pass this course requires acceptably finished coding exercises as well as exercise work and return in time.

5 credits: 27 * 5 = 135 hours

Weekly work amount: 135 hours / 14 weeks = 9.5 hours a week.

Content scheduling

The exercises in this course are done with Python

Objective
After completing the course the student can:
- explain the different phases and main methods of the development of a software product
- explain the concepts class hierarchy, inheritance, and polymorphism, and utilize these in software development
- discuss the possibilities of parallel programming
- apply exception handling mechanisms
- design, implement and document a simple user interface application.

Content
- object-oriented structures
- error handling with exceptions
- threads
- database connection
- software development process and methods
- UML diagrams

Further information

The main information channel is ItsLearning

Evaluation scale

H-5

Assessment methods and criteria

The course contains 8 weekly exercises and an exercise work (that corresponds 4 weekly exercises). They can contain both programming theory and coding.

Each exercise has several tasks, from which points are given. Maksimum points from each exercise is 10 and from all exercises is 120.

Grade is formed based on the number and quality of acceptably finished exercises and the presence at class:

less than 60 points -> grade 0
60 points -> grade 1
72 points -> grade 2
84 points -> grade 3
96 points -> grade 4
108 points -> grade 5
Presence less than 75 % on the Friday lectures (without an acceptable reason) reduces the exercise points by 10%.
Acceptable reason to skip lectures is illness (or sudden tragedy in immediate family). Please inform teacher in advance if you cannot make it to the lecture. Working or holiday trip etc. are not acceptable reasons for absence.

Assessment criteria, fail (0)

Grade is fail if less than 60 points is achieved from exercises and/or exercises are very insufficient or of very poor quality.

Assessment criteria, satisfactory (1-2)

Grade is satisfactory (1-2) if 60 - 71 points is achieved and exercises are done in time. Exercises may contain minor (quality) issues.

Assessment criteria, good (3-4)

Grade is good (3-4) if 72 - 107 points is achieved, exercises are done in time and they are well done.

Assessment criteria, excellent (5)

Grade is excellent (5) if at least 108 points is achieved, exercises are done in time and the quality is excellent.

Materials

Materials in Itslearning

Teaching methods

contact teaching, task-based learning, independent study

Exam schedules

N/A

International connections

The course covers the basic skills of research communication and goes through the thesis process.

Completion alternatives

No alternative methods of attainment

Student workload

The course schedule will be published in Itslearning. Instruction in Finnish and instruction in English in alternate weeks. Typically, the course has 13 sessions (1 x kickoff to the course, 6 x classes in English, 6x classes in Finnish)
Contact classes: 2 x 14h = 28h (14h in Finnish, 14 h in English)
Students' own work : 31h
Students can attend either Finnish or English or both language sessions. However, it is recommended that they attend the classes in the language in which they will write their thesis.

Assessment criteria, approved/failed

Approved: active attendance at least 5 Researc Communication lessons and attendance at least 2 Thesis seminars and a topic paper done.
Failed: Less than 5 active attendances Researc Communication lessons and/or less than 2 attendances Thesis seminars and/or topic paper not done.

Content scheduling

Basics of academic writing
Theses: Types and relevant agreements
The process of thesis writing ( from thesis topic idea to publication)
Basic skills in thesis writing and thesis reporting
Information search

Further information

The course is online course, the link is in Itslearning.
The course is run in parallel in Finnish and English. In English starts in week 2 and is every other week, in Finnish begins in week 5.

Evaluation scale

Hyväksytty/Hylätty

Assessment criteria, fail (0)

Failed: Less than 5 active attendances Researc Communication lessons and/or less than 2 attendances Thesis seminars and/or topic paper not done.

Assessment criteria, satisfactory (1-2)

N/A

Assessment criteria, good (3-4)

N/A

Assessment criteria, excellent (5)

N/A

Objective

The student can communicate in writing in different work-life situations.

Content

The student
- can describe the content and structure of his/her studies, training and work experience
- can describe his/her working environment and operations of a company, products and processes
- can communicate in various business life situations appropriately
- is able to use appropriate vocabulary and phrases when presenting tasks of his/her own field

Materials

- lecturer's material in Itslearning

Exam schedules

written exam

International connections

- lectures and online lessons in Zoom
- written assignments
- online studies

Content scheduling