Master in Data Engineering

Warsaw University of Technology is the premier technical research university in Poland, combining a rich 200-year history with cutting-edge innovation. It is consistently ranked as the top engineering school in the country, attracting the brightest minds from across the globe.

Data Engineering is a master's programme taught in English at Warsaw University of Technology in Warszawa, Poland. The degree runs for four semesters, with yearly tuition of 13080 EUR. Delivered as a Data Science program, the degree gives students in-depth knowledge and skills for processing and analyzing growing volumes of data, covering techniques for both structured and unstructured data. Particular emphasis falls on natural language processing and the analysis of network data, including data from social networks. The programme also builds programming skills in languages commonly used for data processing, especially Python, combined with in-depth experience using Big Data processing platforms such as Apache tools and cloud computing services, including work with major cloud providers. On the analytics side, particular attention goes to machine learning methods, including deep learning and techniques focused on network and text analysis, which feed into broader knowledge of artificial intelligence. The programme brings together key algorithms, methods, languages, and platforms used in data acquisition, storage, processing, analysis, and visualization, paired with hands-on experience solving real-world problems defined by industry experts. Each student selects a scientific advisor from among the academic and research staff, and the final semester is devoted mainly to preparing the master's thesis. Students also have the option to spend a semester studying at a cooperating European university through a student exchange program. Data engineering as a discipline focuses on building the pipelines and infrastructure that make large-scale data analysis possible, and graduates typically pursue careers as data engineers, data scientists, or machine learning engineers across technology, finance, and research-driven industries.