Course detail

Modern Trends in Informatics (in English)

FIT-MTIaAcad. year: 2019/2020

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.

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.

Recommended optional programme components

Not applicable.

Recommended or required reading

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.

Planned learning activities and teaching methods

Not applicable.

Assesment methods and criteria linked to learning outcomes

  • As a mid-term check point (milestone) a detailed outline of the assignment paper as well as an annotated list of the reference material (scientific papers) will need to be delivered.

Exam prerequisites:
  • At least 50 points for the assignment paper surveying recent developments in a chosen computer science area

Language of instruction

English

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.

Classification of course in study plans

  • Programme IT-MGR-2 Master's

    branch MGMe , any year of study, summer semester, 4 credits, optional

  • Programme MITAI Master's

    specialization NADE , any year of study, summer semester, 4 credits, compulsory
    specialization NBIO , any year of study, summer semester, 4 credits, compulsory
    specialization NGRI , any year of study, summer semester, 4 credits, compulsory
    specialization NNET , any year of study, summer semester, 4 credits, compulsory
    specialization NVIZ , any year of study, summer semester, 4 credits, compulsory
    specialization NCPS , any year of study, summer semester, 4 credits, compulsory
    specialization NSEC , any year of study, summer semester, 4 credits, compulsory
    specialization NEMB , any year of study, summer semester, 4 credits, compulsory
    specialization NHPC , any year of study, summer semester, 4 credits, compulsory
    specialization NISD , any year of study, summer semester, 4 credits, compulsory
    specialization NIDE , any year of study, summer semester, 4 credits, compulsory
    specialization NISY , any year of study, summer semester, 4 credits, compulsory
    specialization NMAL , any year of study, summer semester, 4 credits, compulsory
    specialization NMAT , any year of study, summer semester, 4 credits, compulsory
    specialization NSEN , any year of study, summer semester, 4 credits, compulsory
    specialization NVER , any year of study, summer semester, 4 credits, compulsory
    specialization NSPE , any year of study, summer semester, 4 credits, compulsory

  • Programme IT-MGR-1H Master's

    branch MGH , any year of study, summer semester, 4 credits, recommended

Type of course unit

 

Lecture

26 hours, 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

Projects

13 hours, compulsory

Teacher / Lecturer

eLearning