Machine learning in bioengineering

The goal of the course “Machine Learning in Bioengineering” is to study the key principles and tools of machine learning, as well as to develop skills in applying computational methods and modern computer technologies to solve scientific problems in the field of bioengineering. Completing the course will allow students who are not familiar with machine learning to understand the main features and limitations of working with different data formats and various algorithms. The focus is on the basics of applying machine learning methods in different areas of bioengineering, including different types of tasks (classification, regression, etc.) and different data formats (tables, sequences, images), which is reinforced through practical work. As a result of mastering the discipline, students will:

• Gain basic theoretical knowledge and master approaches to solving bioengineering problems using machine learning methods;
• Acquire knowledge of predictive algorithms, as well as their limitations and scope of applicability;
• Develop skills in working with tools and libraries for machine learning;
• Gain experience in solving typical tasks and working with various formats of biological data.

To complete the course, basic knowledge of bioinformatics, statistics, and molecular biology is required. It is recommended to take the inter‑faculty course “Introduction to Programming Using Python” or any other similar course.

Занятия проводятся на кафедре биоинженерии биологического факультета МГУ им. М.В. Ломоносова (Лабораторный корпус Б, ауд. 543)

В программе курса 11 занятий: 7 лекций и 4 практических занятий, а также 6 домашних заданий в Google Colab

Формат проведения: оффлайн

Старт курса: 13 февраля 2025 года

Занятия будут проходить по четвергам с 15:35 до 17:10

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Набор на курс 2025 года закрыт