Topics for Master degree state examination Open Informatics (accreditation 2016 and 2018)
Common part
Polynomial algorithms for standard graph problems. Combinatorial and number-theoretical algorithms, isomorphism, prime numbers. Search trees and their use. Text search based on finite automata. BE4M33PAL
Problem/language complexity classes with respect to the time complexity of their solution and memory complexity including undecidable problems/languages. BE4M01TAL
Combinatorial optimization problems - formulation, complexity analysis, algorithms and example applications. BE4M35KO
Artificial Intelligence
Learnability models: PAC and online. Learnability of conjunctions and disjunctions. Bayesian networks. Reinforcement learning. BE4M36SMU
Resolution in the first order logic, automatic proving. Principles of automatic proving in Boolean domains and in predicate logic. Searching for models in generic domains. BE4M36LUP
Minimizing empirical risk. Maximum likelihood estimation, EM algorithm. Deep networks and their training. Classical and deep neural networks and their learning. BE4M33SSU
Domain independent planning. Features, heuristics and algorithms. BE4M36PUI
Autonomous agents and multiagent systems. Noncooperative game theory. BE4M36MAS
Decision making, planning and coordination of autonomous systems of one or more robots. BE4M36UIR
Computer graphics
Raster graphic. 3D objects and 3D scenes, transformations. Visibility, local illumination methods, shading and shadows. Radiometry, global illumination methods, texturing. BE4M39APG
Data structures for searching in multidimensional spaces. BE4M39DPG
Objects representation and their animation. Tools to support the production process. BE4M39MMA
Basic data structures of computational geometry, methods of their construction, and representation. BE4M39VG
Scientific visualization methods. Information visualization methods. BE4M39VIZ
Spatial geometry, image projection and perspective camera model for 3D reconstruction, virtual reality, visual odometry and SLAM. BE4M33GVG
Human-Computer Interaction
Scientific visualization methods. Information visualization methods. BE4M39VIZ
A formal description of user interfaces. Models of human behavior in relation to user interaction. Formal evaluation and prototyping. BE4M39NUR
User research and its role in HCI. Cognitive psychological concepts and their usage in HCI. BE4M39PUR1
Statistical analysis, models and their assessment. Dimensionality reduction. Clustering. BE4M36SAN
Principles of shape psychology. Essential composition and form principles. BE4M39PTV
The methodology of software testing. Methods for test creation from the application model. Automated testing. BE4M36ZKS
Software Engineering
The methodology of software testing. Methods for test creation from the application model. Automated testing. BE4M36ZKS
Software architectures, their parameters and qualitative metrics. Architectural patterns, styles and standards. BE4M36SWA
Properties of parallel and distributed algorithms. Communication operations for parallel algorithms. Parallel algorithms for linear algebra. BE4M35PAG
Effective algorithms and optimization methods. Data structures, synchronization and multithreaded programs. BE4M36ESW
Big Data concept, basic principles of distributed data processing, types and properties of NoSQL databases. BE4M36DS2
Security analysis of operating systems, development of secure software and web applications security. Analysis of cyberattacks and malware. Security of mobile devices. BE4M36BSY
Computer Vision and Digital Image
Basic data structures of computational geometry, methods of their construction, and representation. BE4M39VG
Image representation for computer vision. Segmentation and image preprocessing methods. BE4M33DZO
Object detection in images. Image matching and correspondence search. BE4M33MPV
Spatial geometry, image projection and perspective camera model for 3D reconstruction, virtual reality, visual odometry and SLAM. BE4M33GVG
Algorithms for 3D geometric model reconstruction from images. BE4M33TDV
Minimizing empirical risk. Maximum likelihood estimation, EM algorithm. Deep networks and their training. Classical and deep neural networks and their learning. BE4M33SSU
Data Science
Statistical analysis, models and their assessment. Dimensionality reduction. Clustering. BE4M36SAN
Scientific visualization methods. Information visualization methods. BE4M39VIZ
Ontologies. Basic principles of ontological engineering, semantic web technologies, basic principles and technologies of linked data. BE4M33OSW
Minimizing empirical risk. Maximum likelihood estimation, EM algorithm. Deep networks and their training. Classical and deep neural networks and their learning. BE4M33SSU
Learnability models: PAC and online. Learnability of conjunctions and disjunctions. Bayesian networks. Reinforcement learning. BE4M36SMU
Big Data concept, basic principles of distributed data processing, types and properties of NoSQL databases. BE4M36DS2
Cyber Security
Statistical analysis, models and their assessment. Dimensionality reduction. Clustering. BE4M36SAN
The methodology of software testing. Methods for test creation from the application model. Automated testing. BE4M36ZKS
Security analysis of operating systems, development of secure software and web applications security. Analysis of cyberattacks and malware. Security of mobile devices. BE4M36BSY
Symmetric and asymmetric cryptography. Basic cryptosystems (RSA, El-Gamal). Number factorisation. Hashing algorithms. BE4M01MKR
Network routing principles. Network transport protocols. Software defined networks. Network function virtualization. A0M32PST
Principles of secure system design. Design and analysis of secure communication protocols, e.g., TLS, mobile telephony and others. Distributed system security. BE4M36KBE
Computer Engineering
Design and implementation of in-chip integrated systems, application specific systems. BE4M34ISC
Advanced architectures of processors, memory and peripheral circuits and multiprocessor computers. BE4M35PAP
I/O and network interfaces of computer and embedded systems, hardware and software implementation. BE4M38KRP
ARM based microcontrollers and signal processors; their functionality. Design and implementation of embedded systems for typical application areas. BE4M38AVS
Properties of parallel and distributed algorithms. Communication operations for parallel algorithms. Parallel algorithms for linear algebra. BE4M35PAG
Effective algorithms and optimization methods. Data structures, synchronization and multithreaded programs. BE4M36ESW
Bioinformatics
Chemical composition of living matter, experimental models and methods, genetic code. BE4M36MBG
Modeling and analysis of biological sequences. BE4M36BIN
Image representation for computer vision. Segmentation and image preprocessing methods. BE4M33DZO
Statistical analysis, models and their assessment. Dimensionality reduction. Clustering. BE4M36SAN
Learnability models: PAC and online. Learnability of conjunctions and disjunctions. Bayesian networks. Reinforcement learning. BE4M36SMU
Minimizing empirical risk. Maximum likelihood estimation, EM algorithm. Deep networks and their training. Classical and deep neural networks and their learning. BE4M33SSU