Syllabus for Artificial Intelligence

Artificiell intelligens

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, Technology 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
  • Revised: 2011-05-30
  • Revised by: The Faculty Board of Science and Technology
  • Applies from: Autumn 2011
  • Entry requirements:

    120 credits including 15 credits in mathematics and 20 credits in computing science, including a second course in programming.

  • Responsible department: Department of Information Technology

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.


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.

Reading list

Reading list

Applies from: Autumn 2012

Some titles may be available electronically through the University library.

  • Russell, Stuart Jonathan; Norvig, Peter Artificial intelligence : a modern approach

    3. ed.: Boston: Pearson Education, cop. 2010

    Find in the library

Last modified: 2022-04-26