Bachelor
2024/2025
Research Seminar "Machine Learning and Applications 1"
Type:
Elective course (Computing and Data Science)
Area of studies:
Applied Mathematics and Information Science
Delivered by:
Big Data and Information Retrieval School
Where:
Faculty of Computer Science
When:
3 year, 1-4 module
Mode of studies:
offline
Open to:
students of one campus
Language:
English
ECTS credits:
3
Course Syllabus
Abstract
The research seminar is aimed at developing the skills of students to participate in research activities, getting acquainted with modern methods of machine learning and their practical application, developing skills in presenting research results and designing presentation materials.
Learning Objectives
- The seminar is designed to facilitate the timely inclusion of students in the research process,
- the development of skills for conducting scientific discussion and presentation of research results.
Expected Learning Outcomes
- Students are well-versed in what is the modern scientific direction of optimization methods
- Students know both proven approaches in classical machine learning and modern research
- Students have a basic idea about the main directions in DL
Interim Assessment
- 2024/2025 1st moduleПравила округления итоговой оценки: Grade_result = 0.4 * Grade_tests + 0.4 * Grade_report + 0.2 * Grade_references Grade_tests - the total score for the tests at the seminars Grade_report - a summary assessment of two scientific presentations Grade_references - the total score for writing reviews on reports All intermediate grades are not rounded. The final score is rounded mathematically.
- 2024/2025 4th moduleПравила округления итоговой оценки: Grade_result = 0.4 * Grade_tests + 0.4 * Grade_report + 0.2 * Grade_references Grade_tests - the total score for the tests at the seminars Grade_report - a summary assessment of two scientific presentations Grade_references - the total score for writing reviews on reports All intermediate grades are not rounded. The final score is rounded mathematically.
