Machine Learning and its Application for Finance

2025/2026

Учебный год

ENG

Обучение ведется на английском языке

3

Кредиты

Кто читает:

Департамент финансов

Статус:

Курс по выбору

Когда читается:

1-й курс, 3 модуль

Преподаватель

Горячев Александр Андреевич

Course Syllabus

Abstract

During this practically oriented data science module students will learn how machine learning uses computers to run predictive models. The main objective is to explore existing data to build new knowledge, forecast future behavior, anticipate outcomes and trends. Explore theory and practice, and work with tools like Python to solve advanced data science problems.

Learning Objectives

• Make students able to collect, store, process and analyze data automatically with the use of scripting languages
• Make students able to develop and apply new research methods of basic machine learning algorithms and ways to collect information using data mining techniques
• Make students able to solve economic, financial and managerial problems using the best practices of data analysis using modern computational tools
• Make students able to identify the data needed for addressing the financial and business objectives

Expected Learning Outcomes

• Able to choose tools, modern technical means and information technologies for processing information in accordance with the assigned scientific task in the field of finance
• Choose methods adequately corresponding to the objectives of a research project
• Collect, store, process and analyze data automatically with the use of scripting languages; develop and apply new research methods of basic machine learning algorithms and ways to collect information using data mining techniques
• Planning and beginning to perform a research project requires an open and innovative mindset.
• Students should know how to: use ICT solutions in solving real-life problems, work together with other team members, develop personal knowledge and skills.

Course Contents

• Foundations of Business Data Analytics
• Descriptive Business Data Analytics
• Predictive Business Data Analytics
• Prescriptive Business Data Analytics
• Machine Learning in Finance: Practical Application
• Machine Learning Algorithms in Finance: Practical Application

Assessment Elements

• Paper test on optimisation modelling theory
• Project on optimisation
• Midterm
• Final test

Interim Assessment

• 2025/2026 3rd module
  0.35 * Final test + 0.15 * Midterm + 0.25 * Paper test on optimisation modelling theory + 0.25 * Project on optimisation

Bibliography

Recommended Core Bibliography

• 9781800206571 - Serg Masís - Interpretable Machine Learning with Python : Learn to Build Interpretable High-performance Models with Hands-on Real-world Examples - 2021 - Packt Publishing - https://search.ebscohost.com/login.aspx?direct=true&db=nlebk&AN=2901980 - nlebk - 2901980
• Choudhury, P., Allen, R. T., & Endres, M. G. (2021). Machine learning for pattern discovery in management research. Strategic Management Journal (John Wiley & Sons, Inc.), 42(1), 30–57. https://doi.org/10.1002/smj.3215

Recommended Additional Bibliography

• Jason Bell. (2020). Machine Learning : Hands-On for Developers and Technical Professionals: Vol. Second edition. Wiley.

Authors

• SOLOVEVA EKATERINA EVGENEVNA