2025/2026
Машинное обучение в финансах
Статус:
Дисциплина общефакультетского пула
Где читается:
Факультет экономических наук
Когда читается:
2 модуль
Охват аудитории:
для своего кампуса
Язык:
английский
Кредиты:
3
Контактные часы:
32
Course Syllabus
Abstract
The aim of this course is to introduce students to the fundamental concepts of supervised machine learning (ML) and its applications in finance. During the lectures, we will cover key ML methods—including classification and regression trees, ensemble techniques, and artificial neural networks—without delving deeply into technical details (though several proofs will be presented, and a solid mathematical background is required to follow the material). In homework assignments, students will learn how to apply these methods to financial problems such as index trading, derivative pricing, volatility forecasting, and portfolio selection. Students will also gain practical experience in working with financial data using ML techniques. In addition, participants will learn basic Python commands and complete practical exercises.