University of Technology
Data Engineering
Master's Programme
Mode of studies: 
full-time programme
4 semesters
Tuition fee: 
5610 euro per semester
Degree awarded: 
Master of Science in Data Science
Application deadline: 
Wednesday, 17 July, 2024
Day of semester start: 
Tuesday, 1 October, 2024
Credits (ECTS): 
Admission requirements: 

Admission requirements are available at: www.students.pw.edu.pl/index.php/How-to-Apply/Admission-to-M.Sc


The Data Science program provides in-depth knowledge and skills needed to process and analyse growing volumes of data. Students learn about data processing and analytical techniques used for structured data and unstructured data. Particular emphasis is placed upon natural language processing and the analysis of network data including the data of social networks. The program also builds programming skills in languages typically used for data processing such as Python. This is combined with in-depth coverage and experience in the use of Big Data processing, including key platforms such as Apache platforms and Cloud Computing, including collaboration with top cloud providers.

As far as data analytics is concerned, particular attention is paid to Machine Learning methods. This includes also deep learning and methods focused on network and text analysis and contributes to the knowledge of Artificial Intelligence.  Hence, the program combines the knowledge of key algorithms, methods, languages and platforms used in data acquisition, storage, processing, analysis and visualisation with hands-on experience in solving real-world problems defined by industry experts.

Each student chooses a scientific advisor from among academic and research staff. Last semester is devoted mainly to M.Sc. thesis preparation. Data Science students can also spend a semester of their studies studying in one of cooperating European universities as a part of student exchange program.

The Data Science team is a group of  researchers with major international collaboration, active in international research community and presenting results of their research at major scientific events.