OPF:INMNPEXS Expert Systems - Course Information

INMNPEXS Expert Systems

Extent and Intensity

2/1/0. 4 credit(s). Type of Completion: zk (examination).

Teacher(s)

Ing. Jan Górecki, Ph.D. (lecturer)
prof. RNDr. Jiří Ivánek, CSc. (lecturer)
Ing. Jan Górecki, Ph.D. (seminar tutor)

Guaranteed by

prof. RNDr. Jiří Ivánek, CSc.
Department of Informatics and Mathematics – School of Business Administration in Karvina
Contact Person: doc. Mgr. Petr Suchánek, Ph.D.

Prerequisites

None

Course Enrolment Limitations

The course is also offered to the students of the fields other than those the course is directly associated with.

fields of study / plans the course is directly associated with

• Business Economics in Trade and Services (programme OPF, N_EKOMAN)
• Managerial Informatics (programme OPF, N_SYSINF)
• Marketing and Management (programme OPF, N_EKOMAN)

Course objectives

The students of the course gain theoretical and practical knowledge in the following fields: artificial intelligence, expert systems and knowledge engineering. The main aim of the course is to explain the use of artificial intelligence and expert systems for supporting of a manager in decision making process in business, marketing, finance, banking, public sector, etc. The students also get in contact with selected tools for creation of expert systems and knowledge discovery from databases.

Syllabus

• 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

Literature

required 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. info
• IVÁNEK, Jiří, Robert KEMPNÝ and Vladimír LAŠ. Znalostní inženýrství. Karviná: Obchodně podnikatelská fakulta v Karviné Slezská univerzita v Opavě, 2007. info
• GIARRATANO, J. C., RILEY, G. Expert Systems: Principles and Programming. PWS Publishing Co. Boston, MA, USA, 2004. ISBN 0-534-38447-1. info
• DVOŘÁK. J. Expertní systémy. FSI VUT, 2004. info
• BERKA, P. Dobývání znalostí z databází. Academia, Praha, 2003. ISBN 80-200-1062-9. info
• JACKSON, P. Introduction to expert systems. Addison-Wesley, Boston, MA, USA, 1998. ISBN 0-201-87686-8. info

recommended literature
• MAŘÍK, V., ŠTĚPÁNKOVÁ, O., LAŽANSKÝ, J. a kol. Umělá inteligence 1-5. Academia, Praha, 1993. info

Teaching methods

Skills demonstration
Seminar classes

Assessment methods

Grade

Language of instruction

Czech

Further comments (probably available only in Czech)

The course can also be completed outside the examination period.

Teacher's information

https://elearning.opf.slu.cz/course/view.php?id=593
attendance in seminars 70 %, seminar paper, final combined exam

Activity	Difficulty [h]
Ostatní studijní zátěž	40
Přednáška	26
Seminář	13
Zkouška	40
Summary	119

• Enrolment Statistics (Winter 2017, recent)
  
• Permalink: https://is.slu.cz/course/opf/winter2017/INMNPEXS