Area of Studies

mathematics, informatics

www

www.sggw.pl/en/for-candidates/recruitment/recruitment-of-foreigners#Inform%20and%20Econ

Department

Faculty of Applied Informatics and Mathematics, Warsaw University of Life Sciences – SGGW

Tuition and Other Fees

Around 8200 PLN per one academic year

Charges for documents, accommodation in a student dormitory, repetition of classes – in accordance with internal regulations.

Application Deadline(s)

Recruitment calendar: https://www.sggw.pl/en/for-candidates/recruitment/recruitment-of-foreigners/recruitment-terms Date of commencement of studies: 1st October.

Course Description

Course Profile

The specialization, realized fully in English, is focused mainly on methods of analysis of the massive datasets. Within this specialization the students will get acquainted with the technologies used for storing, processing and analyzing large data sets and with other quantitative methods of economic analysis, the computer science tools and their practical application. The students will acquire practical skills in building analytical solutions on Big Data platforms. They will become familiar with distributed and parallel processing systems. They will learn how to use basic tools to visualize large data sets. The specialization is focused on the use of high level programming languages, as well as on the design and programming of the databases. The graduates will be able to incorporate the available methods and tools into the computer analysis systems. In general, the Big Data Analytics specialization prepares future analysts of massive datasets that are stored in companies and economical institutions, such as banks, stock markets, telecommunications companies etc.

The detailed list of subjects is as follows:

First year: Mathematical Economics, Dynamic and Financial Econometrics, Microeconometrics, Multidimensional Data Analysis, Software Engineering, Network Services, Foundations of Artificial Intelligence, Advanced Programming, Operational Research – Applications, Survey Sampling, Network Security, Oracle Databases, Processing massive datasets, Facultative Courses, Second Foreign Language, Master Seminar.

Second Year: Theory of Forecasting and Simulations, Basics of Financial Engineering, Statistical Analysis in the Market Research, Advanced data exploration techniques for big data, Deep Learning Methods, Event history analysis, Project Management, Intellectual Property Management, Selected Issues in Sociology and Psychology, Business Ethics, Facultative Courses, Master Seminar, Master Thesis.

The graduates of Big Data Analytics are expected to find job in centers of information processing, IT companies, analysis departments of banks, brokerage companies, investment funds, telecommunications companies, central or local administration, scientific and research institutions.

Education Requirements

- diploma of the first-cycle studies (Bachelor's degree or equivalent) in the field of informatics and econometrics, informatics, mathematics, economics, finance and accounting, logistics;    

 - diploma of related field of the first cycle studies, for which the effects of education are convergent with the learning outcomes expected of the candidates; if the convergence is incomplete, the student will be obliged to supplement the competence gaps by completing the subjects specified during the interview, in an amount not exceeding 30 ECTS, which is the limit of admissible discrepancy (Candidates permanently living outside Poland, who cannot come personally to interview, will be qualified on the basis of the documentation attached to the Candidate Service System);
- in the case of the number of candidates exceeding the admission limit - the average grade from first-cycle studies is taken in to account;                                                                                       
- confirmed knowledge of English language; 

Other Requirements

average grade from first-cycle studies

Contact

Office for Students' Affairs: masterstudies@sggw.pl

Faculty coordinator: joanna_landmesser@sggw.pl