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Study programmes > Second-cycle studies > Data Science and Business Analytics > Data Science and Business Analytics, full-time, second cycle programme (in English)

Data Science and Business Analytics, full-time, second cycle programme (in English) (NW2-PRK-DSBA)

(in Polish: Data Science and Business Analytics, niestacjonarne (wieczorowe), drugiego stopnia (w języku angielskim))
Faculty of Economic Sciences
second cycle programme
full-time, 2-year studies
Language: English

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„Data Science and Business Analytics” is the 2nd program in Eastern Europe in Data analytics in Eduniversal Best Masters Ranking 2022.

The Data Science and Business Analytics Program at the Faculty of Economic Sciences, University of Warsaw is a four-semester program on a full-time basis that provides students with outstanding knowledge of data science.

Data science combines different scientific methods to extract information from data. The Data Science is a rapidly extending part of quantitative analysis, that is highly demanded at the market. Its popularity reflects availability of vast amount of (big) data that used appropriately gives great opportunities for business.

Data Scientist combine broad knowledge and skills of data analysis, econometrics and machine learning, IT programing with soft skills that all together makes them highly desirable experts. Courses are mainly based on R i Python software.

The Data Science and Business Analytics programme gives all necessary knowledge and skills to become very good Data Scientist. In addition to hard IT and analytical courses, the program includes classes in the field of microeconomics, macroeconomics, finance, as well as communication and self-presentation, negotiations or case-study for business.

Career perspectives

Solid theoretical & empirical background will allow graduates to flexibly adapt to the demands of the changing labour market. Their place of employment may in principle be every institution/company where advanced data analysis is needed. Examples of the institutions/companies and their departments where a Data Scientist skills are needed:

  • Financial & Insurance institutions, such as Banks, Brokerage Houses, Leasing Companies, Investment Funds, Insurance companies, FinTech companies etc. (Risk Department, Sales Department, Strategy Department, Marketing Department etc.);
  • Big Corporates (Sales Departments, Marketing Departments, Business Development Departments etc.);
  • Telecommunications companies;
  • Marketing companies;
  • Pharmaceutical companies (Clinical Trials department);
  • Media Houses;
  • Consultancy companies.

Studies in English are payable. Students with best academic and scientific performance may apply for tuition fee waivers as described in the Faculty's Teaching Council resolutions. For more information, please visit our website.

Qualification awarded:

Master's degree in Data Science and Business Analytics

Access to further studies:

doctoral school, non-degree postgraduate education

Learning outcomes

The graduate of this specialization:
- knows and understands in-depth scientific theories in the field of economics, finance, statistics, econometrics, machine learning or programming and the methodology of scientific research in these areas;
- knows and understands the principles of managing intellectual property and information assets, including sources and databases;
- can use the knowledge of mathematics, operations research, statistical and econometric methods, machine learning, and data science to conduct highly specialized quantitative analysis of economic, financial, management issues, and issues of other fields;
- can use advanced IT tools, including selected programming languages ​​from the S, Python, C, C ++, SQL or 4GL group, as well as selected analytical tools from the R, Python or SAS group;
- can combine theoretical knowledge with a comprehensive approach to data processing and analysis, taking into account the methodology of processing large data sets – "big data";
- can conduct research in the field of modelling (econometric, machine learning, time series forecasting, use of quantitative or actuarial methods) in relation to the challenges of planned work in analytical and research departments (financial, insurance, technological or industry institutions, and data-based services);
- can perform complex tasks using methods of acquiring, integrating, processing, and analyzing quantitative and structured as well as qualitative and unstructured data.
- can manage the work of the team, plan the development of themself and others, as well as prepare reports and communicate the results of independent analyses in English;
- can use English at B2 + level, including specialist terminology needed to work and conduct research in the area of ​​Data Science;
- is prepared to critically evaluate the obtained research and analysis results;
- is prepared to plan and organize efficiently their own and teamwork, as well as to quickly self-educate and improve the acquired qualifications; and
- is prepared to follow professional ethical standards.

Admission procedures:

Visit the following page for details on admission procedures: https://irk.uw.edu.pl/