Examination topics in the discipline Computer and information sciences

  • IT and its problem scope. Data, information, knowledge. Data structures. The algorithm and its implementations.
  • Classification of problems in computer science. P and NP problems. Goedel's theorem. Computational and memory complexity. Turing machine and RAM machine.
  • Theoretical foundations of the structure and description of formal languages. Theoretical basis of the construction of translators. Basic problems of mathematical linguistics.
  • Programming paradigms: a declarative, object-oriented, relational, event-based programming models. Examples of languages ​​for these models.
  • Models of concurrency and their properties; properties of concurrent applications.
  • Operating systems: kernel, process, thread, shell. Techniques of building operating systems.
  • Techniques of knowledge representation: ontologies, XML, object and relational model.
  • Databases and their types. Relational model of databases. Modern approaches to creating databases.
  • Computer networks: ISO/ OSI model, physical layer technologies, Ethernet, VLAN, static and dynamic routing, basic routing protocols.
  • Basics of computational methods: computer arithmetic, interpolation, approximation, numerical integration, systems of linear equations, solving differential equations, Fast Fourier Transform.
  • Large-scale calculations; e-infrastructure: types, purpose, examples.
  • Architecture of computers, CPU, GPU, SIMD, MIMD, supercomputers.
  • Models and methods for creating and implementing parallel algorithms; methods to assess their quality.
  • Artificial intelligence: possibilities and limitations. Machine learning methods. Neural networks.
  • Modeling of information systems.
  • Current IT challenges: Internet of Things, big data, quantum computing, large scale systems and calculations.
  • Computer science research methods.