KIUA2002 Application of artificial intelligence/machine learning I

    • Course code
      KIUA2002
    • Number of credits
      15
    • Teaching semester
      2026 Spring, 2027 Spring
    • Language of instruction and examination
      Norwegian/English
    • Campus
      Hamar
    • Required prerequisite knowledge

      None

Course content

This course provides a comprehensive introduction to widely available, popular and useful AI and ML technologies for general use. Students will learn the practical application of these technologies for generalised contexts. This course also provides an understanding of the needs of these contexts in which these technologies can be applied. This will allow students to critically assess the relevance of such technologies for such contexts. Students will also continue to develop general skills in project planning and knowledge sharing.

Learning outcome

Upon successfully passing the course, students will have achieved the following learning outcomes:

Knowledge

Students have:

  • Knowledge about the use of widely available, popular and useful AI and ML technologies for general use.
  • Knowledge about needs such as AI and ML technologies in generalised contexts.
  • Knowledge about such AI and ML technology integration challenges in generalised contexts.
Skills

Students can:

  • Understand and be able to use widely available, popular and useful AI and ML technologies for general use.
  • Identify needs in generalised contexts that can be met using such AI and ML technologies
  • Use such AI/ML technologies and tools in generalised contexts
  • Critically assess the relevance of such AI/ML technologies and tools in generalised contexts
General competence

Students can:

  • Use widely available, popular and useful AI/ML technologies for general purposes to address real-world problems
  • Critically assess the relevance of such AI/ML technologies and tools in real-world contexts.
  • Work in collaborative projects through different activities
Working and teaching methods

The course comprises a combination of lectures, practical exercises, independent study and academic supervision.

Compulsory activities
  • 2 individual pieces of required coursework, compulsory physical attendance on campus.
  • Attendance in classes/teaching sessions is mandatory, where physical attendance on campus is required. There is an 80% attendance requirement in teaching sessions and a 100% attendance requirement in specific learning activities. This is in accordance with the teaching plan for each course in the programme of study.
Examination
Form of assessmentGrading scaleGroupingDuration of assessmentSupport materialsProportionComments
Written assignment
ECTS - A-F
Group
100%
Form of assessment
  • 1 project-based group assignment

Students may choose which language to use for their examination. The available options are Norwegian Bokmål, Norwegian Nynorsk and English.

Permitted examination support material:

  • Literature
  • All printed and written resources
  • Any use of AI-generated text and content must be clarified with the lecturer, clearly labelled and academically justified in the submission

Reading list

Course name in Norwegian Bokmål: 
Applikasjon av kunstig intelligens/maskinlæring I
Faculty
Faculty for Film, TV and Games
Department
Department of Game Development - The Game School
Area of study
Matematisk-naturvitenskapelige fag/informatikk
Programme of study
Bachelor i kunstig intelligens - utvikling og anvendelse
Course level
Intermediate course, level II (200-LN)