Syllabus for Artificial Intelligence
A revised version of the syllabus is available.
- 5 credits
- Course code: 1DL340
- Education cycle: Second cycle
Main field(s) of study and in-depth level:
Computer Science A1N,
- Grading system: Fail (U), Pass (3), Pass with credit (4), Pass with distinction (5)
- Established: 2009-03-12
- Established by: The Faculty Board of Science and Technology
- Applies from: Autumn 2009
120 credits with mathematics 20 credits and Computing Science 30 credits including a second course in Computer Programming.
- Responsible department: Department of Information Technology
In order to pass, the student must be able to
- recognise that a problem is an AI-problem,
- model AI-problems and point out an appropriate solution (for example expert systems, search algorithms, learning),
- describe and use search methods, expert systems, statistical methods and simple methods for learning,
- discuss different definitions of AI, and relate those to the history of AI.
Heuristic search, knowledge representation, expert systems, learning systems.
Applications of AI, for instance in computer games.
Lectures and labs.
Written exam (3 credits) and assignments (2 credits) that are presented orally or in writing.
- Latest syllabus (applies from Autumn 2022)
- Previous syllabus (applies from Autumn 2021)
- Previous syllabus (applies from Spring 2019)
- Previous syllabus (applies from Autumn 2011)
- Previous syllabus (applies from Autumn 2009, version 2)
- Previous syllabus (applies from Autumn 2009, version 1)
The reading list is missing. For further information, please contact the responsible department.
Last modified: 2022-04-26