Data science mathematics 3 (3 cr)
Code: TT00CC19-3005
General information
- Enrollment
-
19.08.2024 - 22.09.2024
Registration for the implementation has ended.
- Timing
-
01.08.2024 - 31.12.2024
Implementation has ended.
- 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 |
|---|---|---|
|
Thu 24.10.2024 time 17:00 - 20:00 (3 h 0 min) |
Hybridiopetus_Data science mathematics 3 TT00CC19-3005 |
Valkea talo Iso Luokka B2.206
Valkea talo Iso Luokka B2.206
|
|
Thu 31.10.2024 time 17:00 - 20:00 (3 h 0 min) |
Hybridiopetus_Data science mathematics 3 TT00CC19-3005 |
Valkea talo Iso Luokka B2.206
Valkea talo Iso Luokka B2.206
|
|
Thu 07.11.2024 time 17:00 - 20:00 (3 h 0 min) |
Hybridiopetus_Data science mathematics 3 TT00CC19-3005 |
Valkea talo Iso Luokka B2.206
Valkea talo Iso Luokka B2.206
|
|
Thu 14.11.2024 time 17:00 - 20:00 (3 h 0 min) |
Hybridiopetus_Data science mathematics 3 TT00CC19-3005 |
Valkea talo Iso Luokka B2.206
Valkea talo Iso Luokka B2.206
|
|
Thu 21.11.2024 time 17:00 - 20:00 (3 h 0 min) |
Hybridiopetus_Data science mathematics 3 TT00CC19-3005 |
Valkea talo Iso Luokka B2.206
Valkea talo Iso Luokka B2.206
|
|
Thu 28.11.2024 time 17:00 - 20:00 (3 h 0 min) |
Hybridiopetus_Data science mathematics 3 TT00CC19-3005 |
Valkea talo Iso Luokka B2.206
Valkea talo Iso Luokka B2.206
|
|
Thu 05.12.2024 time 17:00 - 20:00 (3 h 0 min) |
Hybridiopetus_Data science mathematics 3 TT00CC19-3005 |
Valkea talo Iso Luokka B2.206
Valkea talo Iso Luokka B2.206
|
|
Thu 12.12.2024 time 17:00 - 20:00 (3 h 0 min) |
Hybridiopetus_Data science mathematics 3 TT00CC19-3005 |
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