Магистратура
2025/2026
Семинар наставника
ID 988343
Статус:
Курс обязательный (Стратегическое управление финансами фирмы)
Кто читает:
Школа финансов
Где читается:
Факультет экономических наук
Когда читается:
1-й курс, 1-4 модуль
Охват аудитории:
для своего кампуса
Преподаватели:
Ованесова Юлия Сергеевна
Язык:
английский
Кредиты:
7
Контактные часы:
20
Course Syllabus
Abstract
Financial Data Science is a practice-oriented track focused on the application of machine learning, artificial intelligence, and modern data-analysis tools to financial problems. The track is designed for students who want to work with financial data in a practical setting and understand how ML and AI are used in banking, fintech, investment analysis, risk management, and corporate finance.
During the track, students will work with real or realistic financial datasets and study the full applied workflow: data preparation, feature construction, model selection, validation, interpretation, and implementation. Particular attention will be paid to machine learning for tabular financial data, text analysis and large language models, alternative data, forecasting, classification, and the practical limitations of AI models in finance.
The track is suitable for students who are interested in careers in fintech, banking, quantitative and data-driven finance, financial analytics, and related roles where strong programming and data skills are required. It is especially useful for those who want to build a portfolio of applied projects and learn how to use modern AI tools to solve financial problems rather than study them only at a theoretical level.
Learning Objectives
- To obtain a systematic understanding of modern applications of machine learning, artificial intelligence, and data analysis in finance.
- To form an individual study plan
- To develop a research proposal
Expected Learning Outcomes
- Selecting an individual study plan for the first half of the year
- Selecting an individual study plan for the second half of the year
- Writing a research proposal and research schedule (for the 1st year students)
- Defence of Master's thesis (for the 2nd year students)
Course Contents
- Introduction to the structure of the “Strategic Corporate Finance” study programme
- Monitoring of students' uptake of the learning process
- Mentor's introduction seminar
- Discussion of recent literature on corporate financial decision-making
- Discussion of problems in study or research process
- Discussion of the research proposal
- Introduction to Corporate Finance
- Project Analysis and Evaluation
Assessment Elements
- Attendanceit's very important to participate in all meetings
- Attendance
- Research ProposalFinal report for students
- Attendance
- Attendanceprovide an individual plan for the 2nd year of study
- pre-defence of Master's thesis
Interim Assessment
- 2025/2026 4th module0.2 * Attendance + 0.4 * Research Proposal + 0.2 * Attendance + 0.2 * Attendance
- 2026/2027 4th module0.7 * pre-defence of Master's thesis + 0.3 * Attendance
Bibliography
Recommended Core Bibliography
- Ross, S. A., Westerfield, R., & Jordan, B. D. (2012). Fundamentals of corporate finance. Slovenia, Europe: McGraw-Hill. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.D5D5B17E
Recommended Additional Bibliography
- Berk, J., DeMarzo, P., & Harford, J. V. T. (2014). Fundamentals of Corporate Finance, Global Edition (Vol. Third edition). Harlow: Pearson. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1419502
- Parrino, R., Kidwell, D. S., & Bates, T. (2013). Essentials of Corporate Finance. New York: Wiley. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1639264