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We provide 1st grade studies in:

  • Mathematics (in Polish),
  • Comuter Science (in Polish),
  • Bioinformatics (in Polish),

And 2nd degree studies in:

  • Mathematics (in Polish),
  • Comuter Science (in Polish),
  • Bioinformatics (in Polish),
  • Machine Learning (in English)

Studies in Polish

We require from the candidates language proficiency in Polish at the level of at least B2.

For information on the recruitment process see the Polish version of this website.

Machine Learning, 2nd degree studies, in English

The second degree program in Machine learning offered at the University of Warsaw was created as a response to the rapidly growing interest in information processing technologies in this area. The degree program is designed on the basis of well-functioning and long-established practices in the study field of computer science. The recently developed curriculum has been prepared taking into account current developments in computer science in the area of machine learning and artificial intelligence and their applications in the business.The content is designed to address the needs of both those students who view the knowledge and skills they will acquire during the studies as an asset in their career path, and those particularly gifted in exact science, who are planning a research career. The Faculty of Mathematics, Informatics and Mechanics is recognized and appreciated in the world.

During the second cycle studies, the primary emphasis is on learning creative problem solving, the ability to build generalizations and pose questions. Graduates of the second-cycle studies become proficient not only in the use of selected information processing technologies in the field of machine learning, but they are also able to use the acquired knowledge and skills in applications unrelated to the studied discipline, for example in interdisciplinary research teams. As a result, graduates are prepared for careers that require significant knowledge of machine learning to cope with contemporary challenges facing computer solutions. At the same time, students are included in the research conducted at the university, which prepares the  graduates to conduct scientific research activities and undertake doctoral studies.

Studies in machine learning allow future graduates to acquire advanced knowledge and skills in techniques used in machine learning, including: statistical methods for machine learning, deep neural networks, reinforcement learning, and explanation of results obtained from machine learning procedures. They also become familiar with basic machine learning application domains such as visual recognition, autonomous device control, and natural language processing. As a result, graduates are prepared to design, oversee, and critically analyze IT projects with significant machine learning components, to serve in expert roles in machine learning, and to be leaders beyond the university world. Graduates of the Master of Science in Machine Learning have the knowledge and skills to pursue a third-cycle degree in computer science.

Most classes are held in the building of the Faculty of Mathematics, Informatics and Mechanics, Ochota Campus, 2 Banacha St. Programming classes are held in modern computer laboratories.


First round

  • 6 June–22 June 2023 registration.
  • 23 June 2023 deadline for the registration fee.
  • 29 June 2023, entry exam.
  • 20 July 2023 announcement of  the results.
  • 21-25 July 2023reception of documents.
  • The candidates will be informed by IRK system if they become eliglibe to submit the documents in later dates.

Second round

  • 17 August–8 September 2023 registration.
  • 9 September 2023 deadline for the registration fee.
  • 15 September 2023, entry exam.
  • 21 September 2023 announcement of  the results.
  • 22-25 September 2023 reception of documents.
  • The candidates will be informed by IRK system if they become eliglibe to submit the documents in later dates.

Admission procedure

The qualification is based on the results of the entrance exam.

Form of examination: written, in English

The scope of the examination problems is available here.

A sample exam is available here.

More information can be found in  IRK system.

In case of questions

Please contact us at