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University of Silesia in Katowice

  • Polski
  • English
Faculty of Science and Technology
Logo European City of Science 2024

DISCIPLINE – COMPUTER SCIENCE

The Vinci Summer School in the field of Computer Science allows the participants to explore issues related to the broadly understood artificial intelligence (including artificial intelligence with biometrics) and machine learning as well as data visualisation and creation of artistic patterns. These issues will be addressed both in theory and in practice. Workshops in research teams will take the form of individual work under a supervision of a scientist working at the Institute of Computer Science at the Faculty of Science and Technology of the University of Silesia, specialising in the area chosen by the student. The research will allow students to test their theoretical knowledge in practice. Workshops will be of an experimental nature; the student will have the opportunity to propose and implement new algorithms and verify their accuracy on real data sets from different domains. Such cooperation will allow for the implementation of scientific research with the use of specialised software, under the supervision of a scientist, which in turn should contribute to publishing the research results.

The school’s program includes 76 hours of classes in English with the following elements:

Basic lecture

Basic lecture classes (18 x 45 min). Depending on the target group’s profile and research interests, classes will be carried out on topics related to the discipline chosen by the student: computer science, chemistry, physics, or material science and engineering.

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Workshops

Specialist workshops in research teams (30 x 45 min). Each candidate will declare their willingness to cooperate with a given research team at the recruitment stage, selecting the appropriate topic. These will be stationary classes carried out in modern research laboratories. .

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Online lecture

Online lectures will be conducted by experienced foreign professors specializing in the proposed topics (8 x 45 min).

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