First degree studies
Recruitment subjects: mathematics or computer science or physics
Obtained title: bachelor’s degree
Stationary
Expected admission limit: 90
Beginning of classes: winter semester
Duration of studies: 3 years (6 semesters)
Non-stationary
Expected admission limit: 45
Beginning of classes: winter semester
Duration of studies: 3 years (6 semesters)
Second-cycle studies
Recruitment:
- 1st degree diploma in computer science and econometrics, computer science, economics, finance and accounting, logistics;
- a diploma of another field of first-cycle studies for which the learning outcomes are consistent with the outcomes expected from candidates; if the convergence is incomplete, the student will be required to fill in the competency gaps by completing the subjects indicated during the interview, to the extent not exceeding 30 ECTS, which is the limit of the acceptable discrepancy;
- grade point average for first-cycle studies;
- for candidates for the Big Data Analytics specialization – a diploma of 1st degree studies in computer science and econometrics or a related field and confirmation of knowledge of the English language.
Obtained title: master
Stationary
Estimated admission limit: 60
Beginning of classes: winter semester
Duration of studies: 2 years (4 semesters)
Big Data Analitycs (specialization in English)
Expected admission limit: 15
Beginning of classes: winter semester
Duration of studies: 2 years (4 semesters)
Non-stationary
Expected admission limit: 15
Beginning of classes: winter semester
Duration of studies: 2 years (4 semesters)
Description of direction
The field of study prepares specialists for the analysis and modeling of economic phenomena. The student learns the mathematical foundations of economics and its practical aspects. They acquire the ability to use a wide range of statistical and computational tools in practice. He also acquires IT competences, including programming and its use for calculations in economics.
Graduates have a thorough knowledge of econometrics and computational methods in economics. They master the basics of actuarial methods and insurance market issues. They have practical skills in analyzing, modeling and optimizing economic processes. Their competences also include knowledge of computer techniques such as programming, designing information systems, as well as their use in economic research and management.
Depending on the level of studies, students can broaden their knowledge in the following areas:
- statistics and econometrics,
- financial engineering,
- mass data analysis technologies – big data,
- business intelligence systems,
- advanced data analytics.
Career prospects
Graduates may be employed in:
- analysis departments of banks and financial advisory companies,
- brokerage houses,
- state and local government administration,
- agricultural information processing centers for the purposes of the EU common agricultural policy,
- computer companies,
- scientific and research institutions.