Course details

Modern Trends in Informatics (in English)

MTIa Acad. year 2021/2022 Summer semester 4 credits

Current academic year

The course is based on a series of self-contained lectures focusing on modern trends of computer science. An initial list of topics is given below.


Course coordinator

Language of instruction



Classified Credit

Time span

  • 26 hrs lectures
  • 13 hrs projects

Assessment points

  • 100 pts projects



Subject specific learning outcomes and competences

Students will get acquainted with modern trends of computer science and information technology that have a great potential to impact future development in the field. They will self-study a chosen topic and prepare an overview of the current state of the art and recent advancements.

Thanks to the contacts with experts presenting lectures on their specific domains of interest, students will be able to get an insight into the way researchers and developers think about problems in their respective field. They will also strenghten their ability to get grasp of a new theoretical subjects, to correctly use referred papers and to follow the current development in scientific disciplines.

Learning objectives

To get an overview of novel research and development directions in computer science and information technologies, to gain an insight into modern trends in a wide range of theoretical areas of the computer science and their known and expected applications, to understand basic concepts of the fields and processes influencing their future development.

Why is the course taught

The course reflect the fact that students cannot take part in a large variety of theoretical fields in the course of their two-years Master study. Thus, it offers a kind of tasting of the actual development in the computer science. Students can then decide to continue their interest or even their future research in a particular domain. 

Study literature

  • Michael A. Nielsen and Isaac L. Chuang. 2011. Quantum Computation and Quantum Information: 10th Anniversary Edition (10th ed.). Cambridge University Press.
  • Yampolskiy, R.V., 2018. Artificial Intelligence Safety and Security. Chapman and Hall/CRC.
  • Russell, S.J. and Norvig, P., 2016. Artificial intelligence: a modern approach. Malaysia; Pearson Education Limited.
  • Solomon, L.D., 2017. Synthetic Biology: Science, Business, and Policy. Routledge.

Syllabus of lectures

  1. Quantum computing
  2. Security, safety, and credibility
  3. Recent progress in AI research
  4. Synthetic biology
  5. Machine translation
  6. Astroinformatics
  7. Physical modeling
  8. Continent-scale weather forecast
  9. Automotive driving systems
  10. Medical domain modeling
  11. Algorithmic trading
  12. Brain-computer interfaces
  13. Current and future supercomputers

Progress assessment

  • At the end of most of the lectures, there will be a couple of questions to be answered on the topic. Answers will be assessed and students get points (~10 per lecture). Everybody paying attention to the presentation should be able to answer correctly. 

Exam prerequisites

  • At least 50 points from the tests after lectures (the total for all the lectures will make 100)

Course inclusion in study plans

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