| NUMBER: | 310502 |
| SHORT: | KI |
| MODULBEAUFTRAGTE:R: | Prof. Dr. Asja Fischer |
| LECTURER: | Prof. Dr. Asja Fischer |
| FACULTY: | Fakultät für Informatik |
| LANGUAGE: | English |
| SWS: | 4 SWS |
| CREDITS: | 5 CP |
| WORKLOAD: | 150 h |
| OFFERED IN: | each summer semester |
BESTANDTEILE UND VERANSTALTUNGSART
Artificial Intelligence – Lecture (2 SWS)Artificial Intelligence – Exercise (2 SWS)
EXAMS
| FORM: | schriftlich |
| ANMELDUNG: | eCampus |
| DATE: | 0000-00-00 |
| START: | 00:00:00 |
| DURATION: | 120 min |
| ROOM: |
LERNFORM
The lecture will be held as a seminar with media support, eLearning-supported homework with practical exercises to be implemented on the computer are assigned weekly and discussed in the exercise lesson.
LERNZIELE
After successfully completing the module- students understand the basic procedures and methods of artificial intelligence and can apply them in practice
- the students are able to assess the efficiency of the discussed procedures and can use them successfully to solve specific problems of different application domains.
- the students have mastered the terminology of the subject area
- the students know both industrially and economically relevant fields of application
CONTENT
The lecture gives an overview of important approaches and methods of artificial intelligence. In terms of content, important concepts and ideas such as design principles of intelligent agents, problem solving through search and knowledge-based inference, problem solving in the case of uncertain knowledge, action planning and basic ideas of machine learning are covered. Furthermore, important areas of application and possible uses in practice are to be learned.
REQUIREMENTS CREDITS
Passed final module examination and successful participation in the exercises
RECOMMENDED PRIOR KNOWLEDGE
Solid basic knowledge in mathematics (content of the modules Mathematics 1 - Basics, Mathematics 2 - Algorithms, Mathematics 3 - Applications) and in computer science (content of the modules Computer Science 1 - Programming and Computer Science 2 - Algorithms and data structures)
LITERATURE
1. S. Ruseel und P. Norvig: „Artificial Intelligence: A Modern Approach“, Prentice Hall,3rd edition, 2009
2. W. Ertel: „Grundkurs Künstliche Intelligenz: Eine praxisorientierte Einführung“, 4. Auflage, 2016