Introduction to Big Data Analytics (5 cr)
Code: TX00EX95-3001
General information
- Enrollment
-
06.05.2024 - 20.10.2024
Registration for the implementation has ended.
- Timing
-
21.10.2024 - 15.12.2024
Implementation has ended.
- Number of ECTS credits allocated
- 5 cr
- Local portion
- 5 cr
- Mode of delivery
- On-campus
- Unit
- (2019-2024) School of ICT
- Campus
- Karaportti 2
- Teaching languages
- English
- Seats
- 0 - 35
- Degree programmes
- Degree Programme in Information Technology
Implementation has 15 reservations. Total duration of reservations is 40 h 0 min.
| Time | Topic | Location |
|---|---|---|
|
Wed 23.10.2024 time 13:00 - 15:30 (2 h 30 min) |
Introduction to Big Data Analytics TX00EX95-3001 |
KMC565
Digitila
|
|
Fri 25.10.2024 time 13:00 - 16:00 (3 h 0 min) |
Introduction to Big Data Analytics TX00EX95-3001 |
KME551
Oppimistila
|
|
Wed 30.10.2024 time 13:00 - 15:30 (2 h 30 min) |
Introduction to Big Data Analytics TX00EX95-3001 |
KMC565
Digitila
|
|
Fri 01.11.2024 time 13:00 - 16:00 (3 h 0 min) |
Introduction to Big Data Analytics TX00EX95-3001 |
KME551
Oppimistila
|
|
Wed 06.11.2024 time 13:00 - 15:30 (2 h 30 min) |
Introduction to Big Data Analytics TX00EX95-3001 |
KMC565
Digitila
|
|
Fri 08.11.2024 time 13:00 - 16:00 (3 h 0 min) |
Introduction to Big Data Analytics TX00EX95-3001 |
KME551
Oppimistila
|
|
Wed 13.11.2024 time 13:00 - 15:30 (2 h 30 min) |
Introduction to Big Data Analytics TX00EX95-3001 |
KMC565
Digitila
|
|
Fri 15.11.2024 time 13:00 - 16:00 (3 h 0 min) |
Introduction to Big Data Analytics TX00EX95-3001 |
KME551
Oppimistila
|
|
Wed 20.11.2024 time 13:00 - 15:30 (2 h 30 min) |
Introduction to Big Data Analytics TX00EX95-3001 |
KMC565
Digitila
|
|
Fri 22.11.2024 time 13:00 - 16:00 (3 h 0 min) |
Introduction to Big Data Analytics TX00EX95-3001 |
KME551
Oppimistila
|
|
Wed 27.11.2024 time 13:00 - 15:30 (2 h 30 min) |
Introduction to Big Data Analytics TX00EX95-3001 |
KMC565
Digitila
|
|
Fri 29.11.2024 time 13:00 - 16:00 (3 h 0 min) |
Introduction to Big Data Analytics TX00EX95-3001 |
KME551
Oppimistila
|
|
Wed 04.12.2024 time 13:00 - 15:30 (2 h 30 min) |
Introduction to Big Data Analytics TX00EX95-3001 |
KMC565
Digitila
|
|
Wed 11.12.2024 time 13:00 - 15:00 (2 h 0 min) |
Introduction to Big Data Analytics TX00EX95-3001 |
KMD550
Oppimistila
|
|
Wed 22.01.2025 time 09:30 - 12:00 (2 h 30 min) |
Insinöörimatematiikka TX00CN47-3013 |
KME751
Oppimistila
|
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.