Stud.IP Uni Oldenburg
University of Oldenburg
29.02.2024 12:24:12
inf530 - Artificial Intelligence (Complete module description)
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Module label Artificial Intelligence
Module abbreviation inf530
Credit points 6.0 KP
Workload 180 h
Institute directory Department of Computing Science
Applicability of the module
  • Bachelor's Programme Business Informatics (Bachelor) > Akzentsetzungsbereich Praktische Informatik und Angewandte Informatik
  • Bachelor's Programme Computing Science (Bachelor) > Akzentsetzungsbereich - Wahlbereich Informatik
  • Master of Education Programme (Gymnasium) Computing Science (Master of Education) > Wahlpflichtmodule (Angewandte Informatik)
  • Master of Education Programme (Hauptschule and Realschule) Computing Science (Master of Education) > Mastermodule
  • Master of Education Programme (Vocational and Business Education) Computing Science (Master of Education) > Akzentsetzungsbereich
Responsible persons
  • Sauer, Jürgen (module responsibility)
  • Lehrenden, Die im Modul (authorised to take exams)
Prerequisites
  • Basic knowledge of computer science/business informatics
Skills to be acquired in this module
The students are familiar with the basic concepts of artificial intelligence (AI). They know the concept of rational agents and their behavior. They know how to implement expert systems.They also know basic search and problem solving techniques as well as techniques of knowledge representation. The students can compare different problem solving techniques and use them within other problem contexts. Professional competence
The students:
  • describe the concept of rational agents and their behavior in an agent environemt
  • name and describe the basic search and problem solving techniques of Artificial Intelligence
  • describe and implement expert systems
  • describe basic techniques of knowledge representation
Methodological competence
The students:
  • acknowledge the basic methods of AI
  • transfer AI methods to other application areas
  • evaluate AI methods regarding their appropriateness for destinct problem areas
  • modify and adapt AI methods for specific application areas
Social competence
The students:
  • work in teams
  • present results to groups
Self-competence
The students:
  • reflect their results with regard to the methods of AI
Module contents
  • Overview of AI
  • Rational agents and agent based systems
  • Search and other problem solving techniques
  • Knowledge representation
  • Planning
Recommended reading
  • Russel, S. J.: Norvig, Peter (2012): Artificial Intelligence: A modern Aproach, 3rd Ed.
  • Winston, P.H. (1994): Artificial Intelligence, 3rd Edition
Links
Language of instruction German
Duration (semesters) 1 Semester
Module frequency annual
Module capacity unlimited
Teaching/Learning method 1VL + 1Ü
Previous knowledge Grundkenntnisse Informatik/Wirtschaftsinformatik
Type of course Comment SWS Frequency Workload of compulsory attendance
Lecture 2 SoSe 28
Exercises 2 SoSe 28
Total module attendance time 56 h
Examination Examination times Type of examination
Final exam of module
At the end of the lecture period
Written or oral exam