INMNPEXS Expert Systems

School of Business Administration in Karvina
Winter 2015
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
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
attendance in seminars 70 %, seminar paper, final combined exam
ActivityDifficulty [h]
Ostatní studijní zátěž40
Přednáška26
Seminář13
Zkouška40
Summary119
The course is also listed under the following terms Winter 2014, Winter 2016, Winter 2017, Winter 2018, Winter 2019.
  • Enrolment Statistics (Winter 2015, recent)
  • Permalink: https://is.slu.cz/course/opf/winter2015/INMNPEXS