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, Pass with credit, Pass, Fail
Finalised by
The Faculty Board of Science and Technology, 30 August 2018
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. Proficiency in English equivalent to the Swedish upper secondary course English 6.

Learning outcomes

On completion of the course, the student should 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.

If there are special reasons for doing so, an examiner may make an exception from the method of assessment indicated and allow a student to be assessed by another method. An example of special reasons might be a certificate regarding special pedagogical support from the disability coordinator of the university.

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