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.
Supervisor
Nabízen zahradničním studentům
Všech fakult
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, elective
- 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
- Quantum computing
- Security, safety, and credibility
- Recent progress in AI research
- Synthetic biology
- Machine translation
- Astroinformatics
- Physical modeling
- Continent-scale weather forecast
- Automotive driving systems
- Medical domain modeling
- Algorithmic trading
- Brain-computer interfaces
- Current and future supercomputers