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IoT Big Data and Analytics (5 cr)

Code: 5000BL72-3007

General information


Enrollment
09.12.2024 - 12.01.2025
Registration for the implementation has ended.
Timing
13.01.2025 - 30.04.2025
Implementation is running.
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
10 - 40
Degree programmes
Degree Programme in Information and Communications Technology
Degree Programme in Information and Communication Technology
Teachers
Juha Saarinen
Teacher in charge
Juha Saarinen
Groups
PTIVIS23S
Embedded Software and IoT
Course
5000BL72

Realization has 16 reservations. Total duration of reservations is 39 h 0 min.

Time Topic Location
Fri 17.01.2025 time 08:00 - 10:00
(2 h 0 min)
Lecture, IoT Big Data and Analytics 5000BL72-3007
ICT_B1026_Gamma GAMMA
Fri 17.01.2025 time 13:00 - 16:00
(3 h 0 min)
Labwork, IoT Big Data and Analytics 5000BL72-3007
ICT_C3027 Sulautettujen ohjelmistojen laboratorio/IT
Tue 21.01.2025 time 14:00 - 16:00
(2 h 0 min)
Luento, IoT Big Data and Analytics 5000BL72-3007
EDU_1002 Moriaberg Esitystila byod
Fri 24.01.2025 time 08:00 - 11:00
(3 h 0 min)
Labwork, IoT Big Data and Analytics 5000BL72-3007
ICT_C3027 Sulautettujen ohjelmistojen laboratorio/IT
Tue 28.01.2025 time 14:00 - 16:00
(2 h 0 min)
Lecture, IoT Big Data and Analytics 5000BL72-3007
ICT_C1042_Myy MYY
Fri 31.01.2025 time 08:00 - 11:00
(3 h 0 min)
Labwork, IoT Big Data and Analytics 5000BL72-3007
ICT_C3027 Sulautettujen ohjelmistojen laboratorio/IT
Tue 04.02.2025 time 14:00 - 16:00
(2 h 0 min)
Lecture, IoT Big Data and Analytics 5000BL72-3007
ICT_B1041_Omega OMEGA
Fri 07.02.2025 time 08:00 - 11:00
(3 h 0 min)
Labwork, IoT Big Data and Analytics 5000BL72-3007
ICT_C3027 Sulautettujen ohjelmistojen laboratorio/IT
Tue 11.02.2025 time 14:00 - 16:00
(2 h 0 min)
Lecture, IoT Big Data and Analytics 5000BL72-3007
ICT_B1041_Omega OMEGA
Fri 14.02.2025 time 08:00 - 11:00
(3 h 0 min)
Labwork, IoT Big Data and Analytics 5000BL72-3007
ICT_C3027 Sulautettujen ohjelmistojen laboratorio/IT
Tue 25.02.2025 time 14:00 - 16:00
(2 h 0 min)
Lecture, IoT Big Data and Analytics 5000BL72-3007
ICT_C1042_Myy MYY
Fri 28.02.2025 time 08:00 - 11:00
(3 h 0 min)
Labwork, IoT Big Data and Analytics 5000BL72-3007
ICT_C3027 Sulautettujen ohjelmistojen laboratorio/IT
Tue 04.03.2025 time 14:00 - 16:00
(2 h 0 min)
Luento, IoT Big Data and Analytics 5000BL72-3007
EDU_1002 Moriaberg Esitystila byod
Fri 07.03.2025 time 08:00 - 11:00
(3 h 0 min)
Labwork, IoT Big Data and Analytics 5000BL72-3007
ICT_C3027 Sulautettujen ohjelmistojen laboratorio/IT
Tue 11.03.2025 time 14:00 - 16:00
(2 h 0 min)
Exam, IoT Big Data and Analytics 5000BL72-3007
ICT_B1026_Gamma GAMMA
Thu 03.04.2025 time 14:00 - 16:00
(2 h 0 min)
Exam Retake, IoT Big Data and Analytics 5000BL72-3007
ICT_C3043 Teoriatila muunto
Changes to reservations may be possible.

Evaluation scale

H-5

Content scheduling

1 Data at rest data in motion
2 Process of data analysis
3 Data preparation
4 Basics of descriptive statistics
5 Data visualization
6 Machine learning basics
7 Big data architectures

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

Lecture material
Labwork exercises

Teaching methods

Lab works 7 x 3h, mandatory
Lectures 7 x 2h, mandatory
Self study

Exam schedules

One exam at the end of the course (late March).

Completion alternatives

-

Student workload

lab works 7x3h = 21h
lectures 7x2h = 14h
exam = 2h
self study = 73h
exam preparation 25h
TOTAL 135h

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)

Further information

Course Itslearningn pages.

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