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For Candidates

02
August
2018

Big Data Analytics – study for free

Modern economy is fully supported by the computer science. The financial sector and rural economy are among many social and economical domains currently undergoing deep changes. The mission of the Faculty is to form engineers who understand the rapidly changing contemporary world and analyse it using computer methods and algorithms. The Big Data Analytics specialization plays an important role in this task.

Mission of the specialization

The specialization, realized fully in English, is focused mainly on methods of analysis of the massive datasets. Massive datasets analysis technologies — Big Data — acquaint students with technologies used for storing, processing and analyzing large data sets and with other quantitative methods of economic analysis, as well as related computer science tools and their practical application. The student will acquire practical skills in building analytical solutions on Big Data platforms. He will become familiar with distributed and parallel processing systems, and will be able to use basic tools to visualize large data sets. The specialization is focused on the use of high level programming languages, as well as database design and query programming. The graduate will be able to combine the available methods and tools into the computer analysis systems. Big Data 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, Microeconometrics, Multidimensional Data Analysis, Software Engineering, Computer Networks, Modeling and optimization of business processes, VBA Advanced Programming / Advanced Programming in Java [optional], Dynamic Econometrics, Operational Research – Applications, Survey Sampling, Oracle Databases / Actuarial Methods [optional], Advanced data exploration techniques for big data, Facultative Courses 1, 2, 3, Second Foreign Language, Master Seminar.

Second Year: Theory of Forecasting and Simulations, Basics of financial engineering, Management Information Systems, Processing massive datasets, Project management, Intellectual property management, Statistical Analysis in the Market Research, Event history analysis, Selected issues in sociology and psychology, Business ethics, Facultative Courses 4, 5, 6, Master Seminar, Master Thesis.

Educational outcomes

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

Recruitment requirements

  • diploma of the first-cycle studies (Bachelor's degree or equivalent) in the field of computer science and econometrics, informatics, economics, finance and accounting, logistics, mathematics; 
  • diploma of another 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; 
  • average grade from first-cycle studies;  
  • confirmed knowledge of English – read more 

Duration
The program is divided into four semesters, start 1st October.

Number of places available: 18

Tuition fee:

  • for Polish citizens and foreigners undertaking studies on the rules applicable to Polish nationals (e.g. holders of a valid Polish Charter card), the studies are free of charges (no tuition fee),
  • for non-national undertaking studies on the rules not-applicable to Polish nationals the first edition of studies –  starting in the academic year – 2018/19 is free of charges (no tuition fee) thanks to co-financing from the POWER program – "Success in nature". Scholarships are not provided.

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

Contact: 
Information on the study programme: dr hab. Joanna Landmesser
e-mail: joanna_landmesser@sggw.pl or wzim@sggw.pl
Recruitment: rekrutacja@sggw.pl