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ID1214 Artificial Intelligence and Applied Methods 7.5 credits

The course gives an overview of Artifical Intelligence and Applied Methods.

The focus is on several different areas of Artifical Intelligence with AI-problems, and Methods and includes areas such as: Intelligent /Knowledge-based systems, Agent / multi-agent systems, Natural language processing and strategies.

Course offerings are missing for current or upcoming semesters.
Headings with content from the Course syllabus ID1214 (Autumn 2021–) are denoted with an asterisk ( )

Content and learning outcomes

Course contents

The following fields are treated within the scope of the course:

  • Fundamental AI problems and solutions including search algorithms and planning, knowledge representation forms and knowledge including reasoning strategies, decision support and heuristics.
  • Intelligent agents and multi-agent systems
  • Automatic analysis and generation of natural language.
  • Machine learning and neural networks.

Focus is on artificial intelligence for knowledge-based systems, agent system and strategies.

Intended learning outcomes

After passing the course, the students should be able to:

  • give an account of artificial intelligence and its application areas
  • know and account for artificial intelligence methods and technologies
  • formulate and carry out a well delimited and qualified assignment that applies artificial intelligence techniques.

Course disposition

No information inserted

Literature and preparations

Specific prerequisites

Knowledge and skills in programming, 6 higher education credits, equivalent to completed course DD1310/DD1311/DD1312/DD1314/DD1315/DD1316/DD1318/DD1331/DD100N/ID1018.

Knowledge and skills in functional or parallel programming, 6 higher education credits, equivalent to completed course ID1019/ID1217/DD1396/DD1362.

Active participation in a course offering where the final examination is not yet reported in LADOK is considered equivalent to completion of the course. 

Registering for a course is counted as active participation. 

The term 'final examination' encompasses both the regular examination and the first re-examination.

Recommended prerequisites

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Examination and completion

If the course is discontinued, students may request to be examined during the following two academic years.

Grading scale

A, B, C, D, E, FX, F


  • INL1 - Written assignment, 4.0 credits, grading scale: P, F
  • TEN1 - Examination, 3.5 credits, grading scale: A, B, C, D, E, FX, F

Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.

The examiner may apply another examination format when re-examining individual students.

Written examination. Written assignment that is reported in groups.

Opportunity to complete the requirements via supplementary examination

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Opportunity to raise an approved grade via renewed examination

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Ethical approach

  • All members of a group are responsible for the group's work.
  • In any assessment, every student shall honestly disclose any help received and sources used.
  • In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.

Further information

Course web

Further information about the course can be found on the Course web at the link below. Information on the Course web will later be moved to this site.

Course web ID1214

Offered by

Main field of study


Education cycle

First cycle

Add-on studies

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Anne Håkansson (

Supplementary information

In this course, the EECS code of honor applies, see: