Machine Learning & Data Science
Description: The course is aimed at developing students ' theoretical knowledge and practical skills on the basics of machine learning, mastering the tools, models and methods of machine learning, as well as acquiring the skills of a data scientist and a developer of mathematical models, methods and algorithms for data analysis.
Amount of credits: 6
Пререквизиты:
- Of Informatively-communication technologies
Course Workload:
| Types of classes | hours |
|---|---|
| Lectures | 30 |
| Practical works | |
| Laboratory works | 30 |
| SAWTG (Student Autonomous Work under Teacher Guidance) | 30 |
| SAW (Student autonomous work) | 90 |
| Form of final control | Exam |
| Final assessment method |
Component: Component by selection
Cycle: Profiling disciplines
