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Computer Science
- 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.
Information and communication technology
- 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.