University of Pardubice
Study programmes & Course catalogue
University of Pardubice
Česky
Search
FAQ

Course: Introduction to Artificial Intelligence

« Back
Course title Introduction to Artificial Intelligence
Course code USII/KUUI
Organizational form of instruction Lecture
Level of course Bachelor
Year of study 3
Semester Winter
Number of ECTS credits 4
Language of instruction Czech
Status of course Compulsory, Optional
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
Lecturer(s)
  • Olej Vladimír, prof. Ing. CSc.
  • Hájek Petr, prof. Ing. Ph.D.
  • Ibl Martin, Ing. Ph.D.
Course content
Ever-present (ambient) intelligence. Artificial and computational intelligence areas. Example of a system with artificial intelligence. Informatics and artificial intelligence in knowledge society. Logical programming languages. Simple knowledge system design. Knowledge representation. Binary expert systems. Expert systems with uncertainty. Time series pre-processing. Neural networks - decision support in economics, social and environmental sphere. Simple models of economic models classification and prediction using neural networks.

Learning activities and teaching methods
Monologic (reading, lecture, briefing), Dialogic (discussion, interview, brainstorming), Laboratory work
Learning outcomes
The aim of the course is to provide basic knowledge in the area of artificial and computer intelligence and the possibilities for its use in various areas of social life, especially the economics, social and environmental fields.
The students should be able to understand the areas and methods of artificial and computer intelligence, they should be able to use simple methods and design simple models, as well as be able to work with the knowledge acquired and uncertainty.
Prerequisites
unspecified

Assessment methods and criteria
Oral examination, Written examination, Didactic test, Discussion, Class observation

Completion and successful defence of two projects. Written exam.
Recommended literature
  • KUNCHEVA, L.I. Fuzzy Classifier Design. A Springer Verlag Company, Germany, 2000.. ISBN 80-7194-095.
  • NILSSON, N. J. Artificial Intelligence: A New Synthesis. Morgan Kaufmann, 1998, ISBN 1558604677. A Springer Verlag Company, Germany, 2000.
  • Olej, Vladimír. Úvod do umělé inteligence : moderní přístupy : distanční opora. Pardubice: Univerzita Pardubice, 2010. ISBN 978-80-7395-307-2.
  • Olej, Vladimír. Úvod do umělé inteligence. Pardubice: Univerzita Pardubice, 2009. ISBN 978-80-7395-241-9.
  • OLEJ, V.-PETR, P. Umělá a výpočetní inteligence. část: Fuzzy množiny. Distančné vzdelávanie v systéme eDOCEO - distanční opora, Fakulta ekonomicko - správní, Univerzita Pardubice, Pardubice, 2004, 62 s., ISBN 80 7194-670-2. ISBN 80-7194-688.


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester
Faculty: Faculty of Economics and Administration Study plan (Version): Informatics in Public Administration (2014) Category: Economy 3 Recommended year of study:3, Recommended semester: Winter
Faculty: Faculty of Economics and Administration Study plan (Version): Enterprise Management (2015) Category: Economy 3 Recommended year of study:3, Recommended semester: Winter
Faculty: Faculty of Economics and Administration Study plan (Version): Informatics in Public Administration (2013) Category: Economy 3 Recommended year of study:3, Recommended semester: Winter
Faculty: Faculty of Economics and Administration Study plan (Version): Enterprise Management (2013) Category: Economy 3 Recommended year of study:3, Recommended semester: Winter
Faculty: Faculty of Economics and Administration Study plan (Version): Regional and Information Management (2014) Category: Economy 3 Recommended year of study:3, Recommended semester: Winter
Faculty: Faculty of Economics and Administration Study plan (Version): Enterprise Management (2014) Category: Economy 3 Recommended year of study:3, Recommended semester: Winter
Faculty: Faculty of Economics and Administration Study plan (Version): Regional and Information Management (2013) Category: Economy 3 Recommended year of study:3, Recommended semester: Winter
Faculty: Faculty of Economics and Administration Study plan (Version): Regional and Information Management (2015) Category: Economy 3 Recommended year of study:3, Recommended semester: Winter
Faculty: Faculty of Economics and Administration Study plan (Version): Enterprise Management (2016) Category: Economy 3 Recommended year of study:3, Recommended semester: Winter
Faculty: Faculty of Economics and Administration Study plan (Version): Informatics in Public Administration (2015) Category: Economy 3 Recommended year of study:3, Recommended semester: Winter
Faculty: Faculty of Economics and Administration Study plan (Version): Information and Security Systems (2015) Category: Economy 3 Recommended year of study:3, Recommended semester: Winter
Faculty: Faculty of Economics and Administration Study plan (Version): Information and Security Systems (2013) Category: Economy 3 Recommended year of study:3, Recommended semester: Winter
Faculty: Faculty of Economics and Administration Study plan (Version): Information and Security Systems (2014) Category: Economy 3 Recommended year of study:3, Recommended semester: Winter
University of Pardubice, date of update: 15.06.2024 23:50.