Data science mathematics 3 (3 cr)
Code: TT00CC19-3006
General information
- Enrollment
-
18.08.2025 - 21.09.2025
Registration for introductions has not started yet.
- Timing
-
01.08.2025 - 31.12.2025
Implementation is running.
- Number of ECTS credits allocated
- 3 cr
- Local portion
- 3 cr
- Mode of delivery
- Contact learning
- Unit
- Teknologia
- Teaching languages
- English
- Finnish
- Degree programmes
- Bachelor’s Degree in Information and Communication Technology
Realization has 8 reservations. Total duration of reservations is 24 h 0 min.
| Time | Topic | Location |
|---|---|---|
|
Tue 21.10.2025 time 17:00 - 20:00 (3 h 0 min) |
Datatieteen matematiikka 3, hybridi |
Valkea talo Iso Luokka B2.206
Valkea talo Iso Luokka B2.206
|
|
Tue 28.10.2025 time 17:00 - 20:00 (3 h 0 min) |
Datatieteen matematiikka 3, hybridi |
Valkea talo Iso Luokka B2.206
Valkea talo Iso Luokka B2.206
|
|
Tue 04.11.2025 time 17:00 - 20:00 (3 h 0 min) |
Datatieteen matematiikka 3, hybridi |
Valkea talo Iso Luokka B2.206
Valkea talo Iso Luokka B2.206
|
|
Tue 11.11.2025 time 17:00 - 20:00 (3 h 0 min) |
Datatieteen matematiikka 3, hybridi |
Valkea talo Iso Luokka B2.206
Valkea talo Iso Luokka B2.206
|
|
Tue 18.11.2025 time 17:00 - 20:00 (3 h 0 min) |
Datatieteen matematiikka 3, hybridi |
Valkea talo Iso Luokka B2.206
Valkea talo Iso Luokka B2.206
|
|
Tue 25.11.2025 time 17:00 - 20:00 (3 h 0 min) |
Datatieteen matematiikka 3, hybridi |
Valkea talo Iso Luokka B2.206
Valkea talo Iso Luokka B2.206
|
|
Tue 02.12.2025 time 17:00 - 20:00 (3 h 0 min) |
Datatieteen matematiikka 3, hybridi |
Valkea talo Iso Luokka B2.206
Valkea talo Iso Luokka B2.206
|
|
Tue 09.12.2025 time 17:00 - 20:00 (3 h 0 min) |
Datatieteen matematiikka 3, hybridi |
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 concept of integral and is able to apply it e.g. for distributions of random variables
The student masters the basic concepts of functions of several variables, such as partial derivative and gradient, and is able to apply them in optimization problems, for example.
Execution methods
Lectures and exercises
Accomplishment methods
Exam
Content
- the integral and its applications
- functions of several variables
- optimization
Qualifications
Data science mathematics 1 and 2