The mission of the Department of Data Analysis and Machine Learning of the Financial University is to be an advanced competence center in data analysis, decision-making and financial services based on information processing.
Today, these technologies are changing all areas of human activity, creating new markets and changing the already existing ones.
The main task of the Department is to provide students of Financial University with not only practical skills in using data analysis and machine learning technologies, but also to enable students of the Faculty of Information Technology and Big Data Analysis to actively participate in real technological projects that change the world for the better.
This task cannot be solved if you simply teach by the textbooks – both technologies and business models in finance are developing much faster now than books are being published. To stay in demand, teachers cannot but conduct advanced scientific research. Such studies are actively conducted at the Department of Data Analysis and Machine Learning, and their results form the basis of solutions demanded by the market. You can read more about this in the section “Projects of the Department”.
In total, the Department employs about 90 professors and 10 staff members who implement several of their own undergraduate, graduate and postgraduate educational programs, as well as teach classes in Machine Learning, Data Processing and FinTech at other Faculties of the Financial University.
The main partners of the Department are both foreign and Russian manufacturers of IT solutions, banks, and insurance companies, who help to implement the practical component of the educational process.
Reacting proactively to the development of the digital economy and digitalization of the financial industry, we are constantly updating our educational programs and launching new ones.
Head of the Department
Deputy Head of the Department of Data Analysis and Machine Learning for Organisational Work
Deputy Head of the Department of Data Analysis and Machine Learning for Educational and Methodological Work
Deputy Head of the Department of Data Analysis and Machine Learning for Academic Work
Head of the Scientific Seminar of the Department of Data Analysis and Machine Learning
Deputy Head of the Department of Data Analysis and Machine Learning for Scientific Work