Infopaket

Methods of artificial intelligence

ДВС.3.02.01

Вибіркова дисципліна для ОП

Second

2022/2023

4 Semester

3

PLO1. Be able to use in-depth professional knowledge and practical skills to optimize the design of models of any complexity, to solve specific problems of designing intelligent information systems of different physical natures. PLO3. Gaining knowledge for the ability to evaluate existing technologies and based on analysis to form requirements for the development of advanced information technologies PLO5. Be able to carry out effective communicative activities of the project development team. PLO8. Communicate effectively on information, ideas, problems, and solutions with professionals and society at large. PLO10. Be able to build models of physical and production processes, design storage and data space, and knowledge base, using charting techniques and standards for information systems development.

Full-time form

To successfully study the discipline the student must meet the following requirements: 1. Know chapters on mathematical analysis, basics of artificial intelligence, differential equations, methods for optimizing functions, programming theory, mathematical logic, and mathematical statistics. 2. Be able to: formulate and solve problems of linear programming, modeling of dynamic systems, solve systems of linear algebraic equations with parameters, solve differential equations, and investigate functions and functionals to the extreme. 3. Have the skills to build, analyze, and apply mathematical models in solving applied problems.

The goal of the discipline is for students to master the methods and methods of creating artificial intelligence tools in specialized computer systems, and to obtain information about the basics of artificial intelligence, the basic concepts of pattern recognition systems, and artificial neural networks.

1. Haykin, S. Neural Networks. A Comprehensive Foundation. Second edition. Prentice Hall, New Jersey - (1998). 2. Shatyrko A., Diblik J., Khusainov D., Bashtinec J. Shodimost processov neyrodinamiki v modeli Hopfilda // Naukovo-teoretychniy J. “Shtucniy intelekt”, 2017, № 3-4, C.139-148. ISSN 1561-5359. 3. Khusainov D., Shatyrko A., Puza B., Novotna V., Pylypenko V. Naukovo-teoretychniy J. “Shtucniy intelekt”, 2019’1-2, № 83-84, C. 49-58. ISSN 1561-5359.

Lectures, laboratory work, independent work.

Semester assessment: The maximum number of points that can be obtained by a student is 60 points: Laboratory work: - 40/24 points. Current evaluation - 20/12 points. Final assessment in the form of an exam.

Ukrainian