Course · SFT6186
Artificial Intelligence
Course information
- Course code
- SFT6186
- Credits (ECTS)
- 5
- L + S + Lab
- 15 + 0 + 30
- Year / semester
- Year 2 / semester 3
- Level of course
- Bachelor's degree
- Component
- University component (UC)
- Cycle
- BD
- Final assessment
- Examination
- Educational programme
- 6B06110 Software Engineering
- Curriculum
- Программная инженерия (2025-2029)
Course description
The purpose of the course is to study the basics of artificial intelligence, various types of neural networks and their application in various tasks, machine learning methods, principles of building neural networks. As a result of mastering the discipline, students will gain knowledge in the field of modern models of artificial neural networks, learn how to use them to solve practical problems. Students will have to carry out innovative engineering projects on development and software for various purposes using modern design methods, advanced experience in developing competitive products, analyze and compare them. Students will be able to set tasks and develop algorithms for solving them for the implementation of software implementations of neural networks in order to solve various practical problems. This discipline provides a detailed overview and description of the most important methods of training neural networks of various structures, as well as practical tasks solved by these networks.
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