Introduction to Big Data Analytics (5 ECTS)
Code: TX00EX95-3002
General information
- Enrollment
-
05.05.2025 - 19.10.2025
Enrollment is ongoing
Enroll to the implementation in OMA
- Timing
-
20.10.2025 - 14.12.2025
The implementation has not yet started.
- Number of ECTS credits allocated
- 5 ECTS
- Mode of delivery
- On-campus
- Unit
- School of ICT and Industrial Management
- Campus
- Karaportti 2
- Teaching languages
- English
- Seats
- 0 - 35
- Degree programmes
- Degree Programme in Information Technology
- Teachers
- Rakel Peltola
- Groups
-
tivivaihto_s25Tivi-vaihto, syksy 2025
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ICT23-SI-NSmart IoT Systems: IoT and Networks
- Course
- TX00EX95
Implementation has 16 reservations. Total duration of reservations is 48 h 0 min.
| Time | Topic | Location |
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Mon 20.10.2025 time 13:00 - 16:00 (3 h 0 min) |
Introduction to Big Data Analytics TX00EX95-3002 |
KMD758
Oppimistila
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Thu 23.10.2025 time 13:00 - 16:00 (3 h 0 min) |
Introduction to Big Data Analytics TX00EX95-3002 |
Online
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Mon 27.10.2025 time 13:00 - 16:00 (3 h 0 min) |
Introduction to Big Data Analytics TX00EX95-3002 |
KMD758
Oppimistila
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Thu 30.10.2025 time 13:00 - 16:00 (3 h 0 min) |
Introduction to Big Data Analytics TX00EX95-3002 |
Online
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Mon 03.11.2025 time 13:00 - 16:00 (3 h 0 min) |
Introduction to Big Data Analytics TX00EX95-3002 |
KMD758
Oppimistila
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Thu 06.11.2025 time 13:00 - 16:00 (3 h 0 min) |
Introduction to Big Data Analytics TX00EX95-3002 |
Online
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Mon 10.11.2025 time 13:00 - 16:00 (3 h 0 min) |
Introduction to Big Data Analytics TX00EX95-3002 |
KMD758
Oppimistila
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Thu 13.11.2025 time 13:00 - 16:00 (3 h 0 min) |
Introduction to Big Data Analytics TX00EX95-3002 |
Online
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Mon 17.11.2025 time 13:00 - 16:00 (3 h 0 min) |
Introduction to Big Data Analytics TX00EX95-3002 |
KMD758
Oppimistila
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Thu 20.11.2025 time 13:00 - 16:00 (3 h 0 min) |
Introduction to Big Data Analytics TX00EX95-3002 |
Online
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Mon 24.11.2025 time 13:00 - 16:00 (3 h 0 min) |
Introduction to Big Data Analytics TX00EX95-3002 |
KMD758
Oppimistila
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Thu 27.11.2025 time 13:00 - 16:00 (3 h 0 min) |
Introduction to Big Data Analytics TX00EX95-3002 |
Online
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Mon 01.12.2025 time 13:00 - 16:00 (3 h 0 min) |
Introduction to Big Data Analytics TX00EX95-3002 |
KMD758
Oppimistila
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Thu 04.12.2025 time 13:00 - 16:00 (3 h 0 min) |
Introduction to Big Data Analytics TX00EX95-3002 |
Online
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Mon 08.12.2025 time 13:00 - 16:00 (3 h 0 min) |
Introduction to Big Data Analytics TX00EX95-3002 |
KMD758
Oppimistila
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Thu 11.12.2025 time 13:00 - 16:00 (3 h 0 min) |
Introduction to Big Data Analytics TX00EX95-3002 |
Online
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Objective
After completing this course student knows the concept of big data, basic capabilities of big data and data science methods, is familiar with the storage, retrieval, processing and analysing big data and analysis tools.
Content
• Big data and analytical concepts
• Acquiring, storing and protecting data
• Big data queries
• Big data analysis
Evaluation scale
0-5
Assessment criteria, satisfactory (1)
The student
• has achieved the objectives of the course
• is able to identify, define and use concepts and models in the subject area of the course
• understands the conditions and principles of the development of expertise.
Assessment criteria, good (3)
The student
• has achieved the objectives of the course well, although there are still areas where knowledge and skills need to be improved
• has a good understanding of the concepts and models of the subject matter of the course and is able to carry out a reasoned analysis
• is able to apply what they have learned in learning and working life situations
• understands the importance of expertise in the ICT field and is able to analyse their own expertise.
Assessment criteria, excellent (5)
The student
• has achieved the objectives of the course with excellent marks
• has an excellent command of the concepts and models of the subject matter of the course
• is able to analyse clearly and reasonably and propose practical development measures
• has a good ability to apply what they have learned in learning and working life situations
• is able to analyse expertise in the ICT field and their own development towards expertise.
Assessment criteria, approved/failed
The student
• has achieved the objectives of the course
• is able to identify, define and use concepts and models in the subject area of the course
• understands the conditions and principles of the development of expertise.