Course detail

Modern Trends in Informatics (in English)

FIT-MTIaAcad. year: 2020/2021

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.

Language of instruction

English

Number of ECTS credits

4

Mode of study

Not applicable.

Offered to foreign students

Of all faculties

Learning outcomes of the course unit

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.

Prerequisites

Not applicable.

Co-requisites

Not applicable.

Planned learning activities and teaching methods

Not applicable.

Assesment methods and criteria linked to learning outcomes

  • 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 curriculum

Not applicable.

Work placements

Not applicable.

Aims

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.

Specification of controlled education, way of implementation and compensation for absences

Not applicable.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Not applicable.

Recommended reading

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

Classification of course in study plans

  • Programme MITAI Master's

    specialization NISY , 0 year of study, summer semester, compulsory
    specialization NADE , 0 year of study, summer semester, compulsory
    specialization NBIO , 0 year of study, summer semester, compulsory
    specialization NCPS , 0 year of study, summer semester, compulsory
    specialization NEMB , 0 year of study, summer semester, compulsory
    specialization NHPC , 0 year of study, summer semester, compulsory
    specialization NGRI , 0 year of study, summer semester, compulsory
    specialization NIDE , 0 year of study, summer semester, compulsory
    specialization NISD , 0 year of study, summer semester, compulsory
    specialization NMAL , 0 year of study, summer semester, compulsory
    specialization NMAT , 0 year of study, summer semester, compulsory
    specialization NNET , 0 year of study, summer semester, compulsory
    specialization NSEC , 0 year of study, summer semester, compulsory
    specialization NSEN , 0 year of study, summer semester, compulsory
    specialization NSPE , 0 year of study, summer semester, compulsory
    specialization NVER , 0 year of study, summer semester, compulsory
    specialization NVIZ , 0 year of study, summer semester, compulsory

  • Programme IT-MGR-1H Master's

    branch MGH , 0 year of study, summer semester, recommended course

  • Programme IT-MSC-2 Master's

    branch MGMe , 0 year of study, summer semester, elective

Type of course unit

 

Lecture

26 hod., optionally

Teacher / Lecturer

Syllabus

  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

Project

13 hod., compulsory

Teacher / Lecturer