IoT Big Data and Analytics (5 cr)

Code: 5000BL72-3006

General information

Enrollment: 01.06.2023 - 26.09.2023
Registration for the implementation has ended.

Timing: 25.09.2023 - 31.12.2023
Implementation has ended.

Number of ECTS credits allocated: 5 cr

Local portion: 5 cr

Mode of delivery: Contact learning

Unit: Engineering and Business

Campus: Kupittaa Campus

Teaching languages: English

Seats: 20 - 60

Degree programmes: Degree Programme in Information and Communications Technology; Degree Programme in Information and Communication Technology

Teachers: Juha Saarinen

Teacher in charge: Juha Saarinen

Scheduling groups: Laboratory Group 1 (Koko: 30 . Open UAS : 0.); Laboratory Group 2 (Koko: 30 . Open UAS : 0.)

Groups: ICTMODembeddedSem
MOD Embedded System (International Semester); PTIVIS22S
Embedded Software and IoT

Small groups: Laboratory Group 1; Laboratory Group 2

Course: 5000BL72

No reservations found for realization 5000BL72-3006!

Evaluation scale

H-5

Content scheduling

Chapter 1 Data and the Internet of Things
Chapter 2 Fundamentals of Data Analysis
Chapter 3 Data Analysis
Chapter 4 Advanced Data Analytics and Machine Learning
Chapter 5 Storytelling with Data
Chapter 6 Architecture for Big Data and Data Engineering

Objective

Student knows Basic tools for data analysis
Student can implement data analytics in edge computing
Student knows Basic solutions for big data analysis in cloud

Content

Data at rest and data in motion
Process for data analysis
Data preparation
Basics of descriptive statistics
Data visualization
Machine learning basics
Big data architectures

Materials

Cisco network academy material www.netacad.com

Teaching methods

Self-study network material
Lectures
7 laboratory sessions

Pedagogic approaches and sustainable development

Lab works
Lectures
Self study

Completion alternatives

Student workload

lab works 7x4h = 28h
lectures 6x1h = 6h
exam = 2h
self study = 74h
exam preparation 25h
TOTAL 135h

Arviointimenetelmät ja arvioinnin perusteet

Must pass Final Exam:
60% -> 1
68% -> 2
76% -> 3
84% -> 4
92% -> 5
Mandatory lab works: +/- 2 grades from individual Lab performance
Mandatory lectures, must attend 70%

Hylätty (0)

Failed Final Exam <60%
or
Weak Final exam < 76% + poor lab performance (missing labs, nonprofessional attitude or lack of active problem-solving, missed lectures)

Arviointikriteerit, kiitettävä (5)

Excellent Final Exam >92%
and
expected lab performance (all labs done with average performance)
or
Good Final Exam >76%
and
superb lab performance (all labs done, actively learns new skills outside of the lab scope, is able to help fellow students, attended all lectures)

Qualifications

Basic skills in using both Windows and Linux systems
Basic networking skills (Cisco CCNA1 or similar)
Basic programming skills with some high level programming language (for example Python, Java, C# or similar)
Basic programming skills include (but are not limited to): output formatting, conditional execution, loops, functions/procedures, function parameters and return values, arrays, error handling, testing and good programming policies
Sufficient logical-mathematical thinking skills
Sufficient skills in English language (lectures and all materials are in English)