Course · SFT6540
Machine Learning 2
Course information
- Course code
- SFT6540
- Credits (ECTS)
- 5
- L + S + Lab
- 15 + 0 + 30
- Year / semester
- Year 4 / semester 7
- Level of course
- Bachelor's degree
- Component
- Minor
- Cycle
- PD
- Final assessment
- Examination
- Educational programme
- 6B06106 Computing and software
- Curriculum
- Вычислительная техника и программное обеспечение (2023-2027)
Minor track course.
Course description
The purpose of this course is to learn the basics of machine learning theory, including discriminant, cluster and regression analysis, and to master the skills of practical solutions to data mining problems.
Student workload
| Type of work | Hours per week | Weeks | Total hours per semester |
|---|---|---|---|
| Lectures (L) | 1 | 15 | 15 |
| Laboratory work (Lab) | 2 | 15 | 30 |
| Independent work under instructor supervision | 1 | 15 | 15 |
| Independent student work | 6 | 15 | 90 |
| Total | 150 |
1 credit = 30 academic hours; a semester lasts 15 weeks.
Source: Platonus, working curriculum for the 2026–2027 academic year.
← Programme curriculum