Course: Expert Systems

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Course title Expert Systems
Course code INM/NAEXS
Organizational form of instruction Lecture + Seminary
Level of course Master
Year of study not specified
Semester Winter
Number of ECTS credits 4
Language of instruction English
Status of course Compulsory, Compulsory-optional
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
Lecturer(s)
  • IVÁNEK Jiří, prof. RNDr. CSc.
  • GÓRECKI Jan, Ing. Ph.D.
Course content
1. Artificial intelligence. 2. The research domains of artificial intelligence. 3. Knowledge representation 4. Expert systems. 5. Presentation of expert system. 6. Creation and architecture of an expert system. 7. Knowledge extraction 8. Case study 9. Dealing with uncertainty and vagueness 10. Fuzzy sets 11. Data mining 12. Decision trees 13. Association rules

Learning activities and teaching methods
Skills demonstration, Seminar classes
  • unspecified - 26 hours per semester
  • unspecified - 40 hours per semester
  • unspecified - 40 hours per semester
  • unspecified - 13 hours per semester
Recommended literature
  • CLARK, B., FOKOUE, E., ZHANG, H. H. Principles and theory for data mining and machine learning. Springer, New York, 2009. ISBN 978-0-387-98134-5.
  • GIARRATANO, J. C., RILEY, G. Expert Systems: Principles and Programming. PWS Publishing Co. Boston, MA, USA, 2004. ISBN 0-534-38447-1.
  • JACKSON, P. Introduction to expert systems. Addison-Wesley, Boston, MA, USA, 1998. ISBN 0-201-87686-8.


Study plans that include the course
Faculty Study plan (Version) Branch of study Category Recommended year of study Recommended semester
School of Business Administration in Karvina Business Economic in Trade and Services (13) Economy 2 Winter
School of Business Administration in Karvina Managerial Informatics (13) Economy 1 Winter