Fundamentals of artificial intelligence (121 Software engineering)

Type: For the student's choice

Department: optoelectronics and information technologies




SemesterAmount of hoursLecturerGroup(s)
532Associate Professor Hrabovskyi V. A.ФеП-31

Laboratory works

SemesterAmount of hoursGroupTeacher(s)
532ФеП-31Associate Professor Hrabovskyi V. A.

Опис навчальної дисципліни

The discipline “Fundamentals of Artificial Intelligence” is designed to study
the basics of artificial intelligence and understanding the main approaches used to create its systems. The role of knowledge, peculiarities of its acquisition, representation, and presentation in different approaches to
in the creation of AI systems and their use. The features of
of building one of the most common types of AI systems – “classical”
expert systems, as well as modern approaches to the creation of such systems
– in particular, the role and importance of using artificial neural networks in modern artificial
artificial neural networks, machine and deep learning, and genetic algorithms in modern AI systems. Attention is drawn to some hardware problems that arise in the process of development of scientific progress and artificial
intelligence as an integral part of it, and possible ways and approaches to solve them.

Recommended Literature

  1. Stuart J. Russell and Peter Norvig. Artificial Intelligence. A Modern Approach. Third Edition – Pearson Ed., 2010. – 1151 p.
  2. Joseph C. Giarratano and Gary D. Riley. Expert Systems: Principles and Programming. Fourth Edition. – Course Technology, Boston, MA, 2004. – 856 p.
  3. Peter Flach. Machine Learning. The Art and Science of Algorithms that Make Sense of Data – Cambridge University Press, Edition 2012. – 416 p.
  4. Ian Goodfellow, Yoshua Bengio, and Aaron Courville:Deep learning. – The MIT Press, 2016. – 800 p.
  5. Eyal Wirsansky. Hands-On Genetic Algorithms with Python – Birmingham – Mumbai, 2020. – 334


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