Data science mathematics 1 (3cr)
Code: TT00CC17-3007
General information
- Enrollment
- 30.12.2025 - 26.01.2026
- Registration for introductions has not started yet.
- Timing
- 01.01.2026 - 31.07.2026
- The implementation has not yet started.
- Number of ECTS credits allocated
- 3 cr
- Unit
- Teknologia
- Teaching languages
- Finnish
- Degree programmes
- Bachelor’s Degree in Information and Communication Technology
Realization has 7 reservations. Total duration of reservations is 21 h 0 min.
| Time | Topic | Location |
|---|---|---|
|
Wed 14.01.2026 time 17:00 - 20:00 (3 h 0 min) |
Hybridi-opetus_Datatieteen matematiikka 1 TT00CC17-3007 |
Valkea talo Iso Luokka B2.206
Valkea talo Iso Luokka B2.206
|
|
Wed 21.01.2026 time 17:00 - 20:00 (3 h 0 min) |
Hybridi-opetus_Datatieteen matematiikka 1 TT00CC17-3007 |
Valkea talo Iso Luokka B2.206
Valkea talo Iso Luokka B2.206
|
|
Wed 28.01.2026 time 17:00 - 20:00 (3 h 0 min) |
Hybridi-opetus_Datatieteen matematiikka 1 TT00CC17-3007 |
Valkea talo Iso Luokka B2.206
Valkea talo Iso Luokka B2.206
|
|
Wed 04.02.2026 time 17:00 - 20:00 (3 h 0 min) |
Hybridi-opetus_Datatieteen matematiikka 1 TT00CC17-3007 |
Valkea talo Iso Luokka B2.206
Valkea talo Iso Luokka B2.206
|
|
Wed 11.02.2026 time 17:00 - 20:00 (3 h 0 min) |
Hybridi-opetus_Datatieteen matematiikka 1 TT00CC17-3007 |
Valkea talo Iso Luokka B2.206
Valkea talo Iso Luokka B2.206
|
|
Wed 18.02.2026 time 17:00 - 20:00 (3 h 0 min) |
Hybridi-opetus_Datatieteen matematiikka 1 TT00CC17-3007 |
Valkea talo Iso Luokka B2.206
Valkea talo Iso Luokka B2.206
|
|
Wed 25.02.2026 time 17:00 - 20:00 (3 h 0 min) |
Hybridi-opetus_Datatieteen matematiikka 1 TT00CC17-3007 |
Valkea talo Iso Luokka B2.206
Valkea talo Iso Luokka B2.206
|
Changes to reservations may be possible.
Evaluation scale
0 - 5
Objective
The student masters the basic concepts of probability calculation and knows how to apply them to practical problems.
The student masters the basic concepts and methods of statistics and is able to apply them in data analysis.
Execution methods
Lectures and exercises.
Accomplishment methods
Exam
Content
- basics of probability calculation
- random variables
- Bayesian networks
- basics of statistics