Artificial intelligence systems (122 Computer Science)

Type: Normative

Department: optoelectronics and information technologies




SemesterAmount of hoursLecturerGroup(s)
832Associate Professor Hrabovskyi V. A.ФеІ-43

Laboratory works

SemesterAmount of hoursGroupTeacher(s)
832ФеІ-43Associate Professor Hrabovskyi V. A.
Associate Professor Ivan Katerynchuk
Dufanets M. V.

Опис навчальної дисципліни

Summary of the subject:

The main tasks of studying the discipline “Methods and Systems of Artificial Intelligence” are to provide students with knowledge of the general state of artificial intelligence, methods and tools used in the creation of artificial intelligence systems, modern approaches to their creation and to develop skills in their practical use. The approaches used in the development of AI systems, as well as the corresponding tools for their creation, are considered. Considerable attention is paid to the methods of obtaining, processing and presenting knowledge, as well as modern artificial intelligence technologies.

Learning outcomes:

know: basic concepts, definitions and problems related to artificial intelligence systems; history of the emergence and development of artificial intelligence; ways of presenting an intellectual task and methods of finding solutions; the role and features of knowledge representation in artificial intelligence systems; problems that arise in knowledge-based systems; algorithms used in the creation of artificial intelligence systems; current trends and approaches to the creation of artificial intelligence systems.

be able to: use the acquired knowledge to solve applied problems using artificial intelligence systems; choose and justify the method of representing an intellectual task necessary to solve a specific problem; use distributed information environments to obtain the necessary information.

Recommended Literature

  • Russell Stewart, Norvig Peter. Artificial Intelligence: A Modern Approach, 2nd ed.: Per. with Engl. – M.: Publishing House “William”, 2006. – 1408 с.
  • Giarratano D., Riley G. Expert Systems: Principles of Development and Programming, 4th ed.: Per. with English. – M.: Publishing House “William”, 2007. – 1152 с.
  • Flach P. Machine Learning. Science and Art of Building Algorithms that Extract Knowledge from Data. – Moscow: DMK Press, 2015. – 400 с.
  • Goodfellow Y., Bengio I., Courville A. Deep Learning / translated from English by A. A. Slinkin. – 2nd edition, revised. – Moscow: DMK Press, 2018. – 652 с.
  • Rutkowska D., Pilinski M., Rutkowski L. Neural Networks, Genetic Algorithms and Fuzzy Systems: Per. with Polish. I. D. Rudinsky. – Moscow: Hot Line-Telecom, 2006. – 452 c.
  • Galushkin A.I. Neurocomputers. Book 3: Textbook for universities / General ed. by A. I. Galushkin. – M: IPRZHR, 2000. – 528 с.
  • Ruchkin, V.N.; Fulin, V.A. Universal artificial intelligence and expert systems. / SPb., “BHV-Peterburg”, 2009. – 240 с


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