Deep Learning

2024/2025

Academic Year

ENG

Instruction in English

6

ECTS credits

Category 'Best Course for Career Development'

Category 'Best Course for Broadening Horizons and Diversity of Knowledge and Skills'

Category 'Best Course for New Knowledge and Skills'

Delivered at:

School of Data Analysis and Artificial Intelligence

Course type:

Compulsory course

When:

2 year, 1, 2 module

Instructor

Ratnikov, Fedor

Course Syllabus

Abstract

The proposed course is dedicated to the methods of "deep learning" — neural network methods of machine learning that have sparked a surge of development in several applied fields. Primarily, the course aims to develop students' skills in solving practical problems using deep neural networks. In recent years, deep learning methods have firmly established themselves in various applied areas, such as: - Computer Vision: recognizing visual patterns, segmentation, synthesizing images from text descriptions; - Text Processing: sentiment analysis, question-answer systems, machine translation, large language models; - Speech Processing: recognition, synthesis, classification of accents, tones, etc.; - Robotics: optimizing behavior strategies, Reinforcement Learning. In this course, students are briefly introduced to the applications of neural networks in all these