Courses
2024/2025
Deep Learning for Graph Data Analysis
Type:
Mago-Lego
Delivered by:
Big Data and Information Retrieval School
When:
1, 2 module
Open to:
students of one campus
Language:
Russian
Bachelor
2024/2025
Deep Learning for Natural Language Processing
Type:
Elective course (Applied Mathematics and Information Science)
Area of studies:
Applied Mathematics and Information Science
Delivered by:
Big Data and Information Retrieval School
Where:
Faculty of Computer Science
When:
4 year, 1, 2 module
Mode of studies:
offline
Open to:
students of all HSE University campuses
Language:
Russian
ECTS credits:
5
Bachelor
2024/2025
Deep Learning for Natural Language Processing
Type:
Compulsory 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:
4 year, 1, 2 module
Mode of studies:
offline
Open to:
students of one campus
Language:
Russian
ECTS credits:
5
Master
2024/2025
Deep Learning for Natural Language Processing
Type:
Elective course (Data Analysis in Development)
Area of studies:
Applied Mathematics and Informatics
Delivered by:
Big Data and Information Retrieval School
Where:
Faculty of Computer Science
When:
2 year, 2 module
Mode of studies:
offline
Open to:
students of one campus
Instructors:
Никонов Максим Викторович
Language:
Russian
ECTS credits:
3
2024/2025
Deep Learning for Natural Language Processing
Type:
Mago-Lego
Delivered by:
Big Data and Information Retrieval School
When:
2 module
Open to:
students of one campus
Instructors:
Никонов Максим Викторович
Language:
Russian
ECTS credits:
3
2024/2025
Deep Learning for Natural Language Processing
Type:
Mago-Lego
Delivered by:
Joint Department with MTS
When:
3, 4 module
Open to:
students of one campus
Instructors:
Малых Валентин Андреевич
Language:
Russian
ECTS credits:
6
Master
2024/2025
Deep Learning for Natural Language Processing
Type:
Compulsory course (Research and Entrepreneurship in Artificial Intelligence)
Area of studies:
Applied Mathematics and Informatics
Delivered by:
Joint Department with MTS
Where:
Faculty of Computer Science
When:
1 year, 3, 4 module
Mode of studies:
offline
Open to:
students of one campus
Instructors:
Малых Валентин Андреевич
Language:
Russian
ECTS credits:
6
Bachelor
2024/2025
Deep Learning for Natural Language Processing
Type:
Elective course (Economics)
Delivered by:
Big Data and Information Retrieval School
When:
4 year, 1, 2 module
Open to:
students of all HSE University campuses
Language:
Russian
Master
2024/2025
Deep Learning for Natural Language Processing
Type:
Elective course (Math of Machine Learning)
When:
1 year, 4 module
Open to:
students of one campus
Language:
English
2024/2025
Deep Learning for Natural Language Processing
Type:
Mago-Lego
When:
4 module
Open to:
students of one campus
Language:
Russian
Bachelor
2024/2025
Deep Learning for Sound Processing
Type:
Elective course (Applied Mathematics and Information Science)
Area of studies:
Applied Mathematics and Information Science
Delivered by:
Big Data and Information Retrieval School
Where:
Faculty of Computer Science
When:
4 year, 1, 2 module
Mode of studies:
offline
Open to:
students of one campus
Instructors:
Aibek Alanov,
Maxim Kaledin,
Федоров Григорий Валерьевич,
Гринберг Петр Маркович,
Федоров Григорий Валерьевич,
Гринберг Петр Маркович
Language:
Russian
ECTS credits:
5
2024/2025
Deep Learning for Sound Processing
Type:
Mago-Lego
Delivered by:
Joint Department with Sberbank ‘Financial Technologies and Data Analysis’
When:
2 module
Open to:
students of one campus
Instructors:
Жестков Борис Григорьевич
Language:
Russian
ECTS credits:
3
Bachelor
2024/2025
Deep Learning Methods in Natural Sciences
Type:
Elective course (Economics and Data Science)
Area of studies:
Applied Mathematics and Information Science
Delivered by:
Big Data and Information Retrieval School
Where:
Faculty of Economic Sciences
When:
3 year, 3, 4 module
Mode of studies:
offline
Open to:
students of one campus
Language:
Russian
ECTS credits:
6
Bachelor
2024/2025
Deep Learning Methods in Natural Sciences
Type:
Elective course (Applied Mathematics and Information 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, 3, 4 module
Mode of studies:
offline
Open to:
students of one campus
Language:
Russian
ECTS credits:
6
Master
2024/2025
Deep Vision and Graphics
Type:
Elective course (Modern Computer Science)
Area of studies:
Applied Mathematics and Informatics
Delivered by:
Joint Department with Yandex
Where:
Faculty of Computer Science
When:
1 year, 1, 2 module
Mode of studies:
offline
Open to:
students of one campus
Language:
Russian
ECTS credits:
6
2024/2025
Deep Vision and Graphics
Type:
Mago-Lego
Delivered by:
Joint Department with Yandex
When:
1, 2 module
Open to:
students of one campus
Language:
Russian
ECTS credits:
6
Bachelor
2024/2025
Democracy and Democratization
Type:
Compulsory course
Area of studies:
Public Policy and Social Sciences
Delivered by:
Faculty of World Economy and International Affairs
When:
4 year, 1, 2 module
Mode of studies:
offline
Open to:
students of one campus
Instructors:
Iryna Zhyrun
Language:
English
ECTS credits:
4
Bachelor
2024/2025
Democracy and Democratization
Type:
Compulsory course
Area of studies:
International Relations
Delivered by:
Faculty of World Economy and International Affairs
When:
4 year, 1, 2 module
Mode of studies:
offline
Open to:
students of one campus
Instructors:
Iryna Zhyrun
Language:
English
ECTS credits:
4
Master
2024/2025
Demographic Analysis and Forecasting
Type:
Elective course (Statistical Analysis in Economics)
Area of studies:
Economics
Delivered by:
Department of Statistics and Data Analysis
Where:
Faculty of Economic Sciences
When:
2 year, 3 module
Mode of studies:
offline
Open to:
students of one campus
Language:
Russian
ECTS credits:
3
2024/2025
Demographic Analysis and Forecasting
Type:
Mago-Lego
Delivered by:
Department of Statistics and Data Analysis
When:
3 module
Open to:
students of one campus
Language:
Russian
ECTS credits:
3