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, Technology A1N
Grading system
Fail (U), Pass (3), Pass with credit (4), Pass with distinction (5)
Finalised by
The Faculty Board of Science and Technology, 30 May 2011
Responsible department
Department of Information Technology

Entry requirements

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

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