Master in Finance and Data Analytics  (MFDA) is a two-year English-language Master's degree programme that is designed to pair the key areas of finance and data analytics. The programme takes a data driven approach to analysis of financial markets and organisational information covering key theoretical principles of finance, financial modeling and financial markets to prepare students for a dynamic career in finance, banking and a range of other sectors.  
Focusing on modern statistical analysis, data modeling, programming, big data and machine learning techniques, program equips the student with a thorough understanding and advanced skills in theoretical and applied finance with emphasis on computational aspects of the problems. 

Programme's graduates will gain quantitative, statistical and technical skills crucial for modern finance and will have the expertise to independently define and creatively solve broad variety of theoretical as well as practical problems. 

Emphasis is put on advanced econometrics, statistical methods and data analysis and applicants must have solid background in Mathematics as well as good command of English. Courses are taught both by faculty members of the Institute of Economic Studies (IES) and external professionals from international institutions, central banks and financial industry. Students are exposed to detailed and advanced knowledge of both financial theory and applied financial methods, with focus on computational aspects of the methods. In particular, courses include Big Data analysis, modern approaches to asset pricing using statistical learning, understanding of financial instruments, advanced econometrics, behavioral finance and time series analysis.

BASIC INFORMATION 

Programme Duration: 2 years
Language of Instruction: English

Programme Director: doc. PhDr. Jozef Baruník, Ph.D  
Programme Coordinator: PhDr. František Čech Ph.D. 

Tuition Fee: 7 000 EUR per year

Reduction or Waiving the Fee:
The Faculty of Social Sciences offers a set of scholarships and fee reductions. Conditions and terms can be found here.

Study Prerequisites: The programme is open to students who have completed a Bachelor’s degree (or equivalent). Applicants with Bachelor degrees in economics, finance, business studies, mathematics, physics, or technical fields are especially welcomed. Applicants are required to have an excellent analytical quantitative skills. They should have completed at least two courses in two terms of Bachelor level mathematics. Applicants should be familiar with the following topics of calculus and linear algebra: functions, limits, derivatives, partial derivatives, optimization techniques, matrix algebra, and differential and difference equations. They should have an introductory-level understanding of probability distributions, hypothesis testing, linear regressions, and the OLS estimation method. Prior knowledge of economics or finance is an advantage, but it is not required.