Introduction to Computational Intelligence 2-IKV-115/15

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Course name and code: Introduction to Computational Intelligence (2-IKV-115/15)
Prerequisite courses: none
Available in/recommended study year: Winter semester / 1
Form and # of hours/week: L - lecture (2), S - seminar (1)
Credits: 5
Evaluation (semester/exam): 70/30
Course webpage:
Information sheet: 2-IKV-115/15 information sheet
Teacher(s): prof. Ing. Igor Farkaš, Dr.

Short description:

The course objectives are to make the students familiar with basic principles of various computational methods of data processing that can commonly be called computational intelligence (CI). This includes mainly bottom-up approaches to solutions of (hard) problems based on various heuristics (soft computing), rather than exact approaches of traditional artificial intelligence based on logic (hard computing). Examples of CI are nature-inspired methods (artificial neural networks, evolutionary algorithms, fuzzy systems), as well as probabilistic methods and reinforcement learning. After the course the students will be able to conceptually understand the important terms and algorithms of CI, and choose appropriate method(s) for a given task. The theoretical introduction is combined with practical examples.

Offered in these study programs: Obligatory in Master program in Cognitive Science

Recommendations: none

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