Artificial Intelligence
5 credits
Syllabus, Master's level, 1DL340
A revised version of the syllabus is available.
- Code
- 1DL340
- Education cycle
- Second cycle
- Main field(s) of study and in-depth level
- Computer Science A1N, Data Science A1N, Technology A1N
- Grading system
- Pass with distinction (5), Pass with credit (4), Pass (3), Fail (U)
- Finalised by
- The Faculty Board of Science and Technology, 12 March 2009
- Responsible department
- Department of Information Technology
Entry requirements
120 credits with mathematics 20 credits and Computing Science 30 credits including a second course in Computer Programming.
Learning outcomes
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.
Content
Heuristic search, knowledge representation, expert systems, learning systems.
Applications of AI, for instance in computer games.
Instruction
Lectures and labs.
Assessment
Written exam (3 credits) and assignments (2 credits) that are presented orally or in writing.