Course · SFT6508
Machine Learning 1
Course information
- Course code
- SFT6508
- Credits (ECTS)
- 5
- L + S + Lab
- 15 + 0 + 30
- Year / semester
- Year 3 / semester 6
- 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 (2024-2028)
Minor track course.
Course description
The course introduces students to the theoretical foundations and algorithms of machine learning, their possible practical implementations and applications in solving real problems. Within the framework of this course, students should get an idea of the problems solved with the help of the theory under consideration, and the principles of constructing some basic classifiers.
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