KIUA2014 Artificial intelligence in practice

    • Course code
      KIUA2014
    • Number of credits
      10
    • Teaching semester
      2026 Autumn
    • Language of instruction
      Norwegian/English
    • Campus
      Hamar
    • Required prerequisite knowledge

      None

Course content

The course will provide students with the opportunity to work in professional environments on development and/or research tasks or to conduct their own design project. Professional environments may include companies or research or development communities at INN University. Students will choose their own specialisation. The chosen area could be the application/development of AI in education, finance, sports science, biotechnology, agriculture, emergency preparedness, or audiovisual media such as gaming, TV and film, etc. The course will prepare students for work with AI-driven tools in professional environments and/or strengthen project-based approaches in collaboration with others.

Learning Outcome

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

Knowledge

The student will have

  • excellent knowledge of the possibilities for applied AI in a chosen field
  • in-depth knowledge of current practices, possibilities and challenges linked to the use of AI
Skills

The student will be able to

  • independently experiment with and evaluate different AI-driven tools in a chosen context
  • apply theoretical perspectives from the chosen field to evaluate and analyse possible consequences of AI
  • evaluate and discuss ethical and legal issues, such as security and privacy within the chosen context
General competence

The student will be able to

  • communicate coherently, clearly and understandably on issues linked to the use of artificial intelligence in the chosen field/context
  • use their AI and ML skills to solve challenges in the chosen field/context
  • exchange views and experiences with others
  • communicate key subject matter in writing and orally
  • acquire new knowledge linked to the chosen topics and seek and accept supervision
Teaching and working methods

Working methods will include problem-based and project-based learning in groups or individually through independent study, presentations and academic supervision. The Canvas communication platform will be used in teaching, as well as a broad range of digital platforms and programs, specifically programs based on machine learning and large language models. 

Required coursework
  • approved curriculum and project outline as chosen by the student

Compulsory assignments can be executed and written in Norwegian Bokmål, Nynorsk or English. 

Assessments
Form of assessmentGrading scaleGroupingDuration of assessmentSupport materialsProportionComment
Written assignment
ECTS - A-F
Group/Individual
100
Form of assessment
  • individual or group-based project assignment

Performance is assessed using a grading scale from A to F, where E is the lowest passing grade.

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

 

Permitted aids:

  • Literature
  • All printed and written resources
  • AI-generated text and content must be clearly labelled and academically justified.
Course name in Norwegian Bokmål: 
Kunstig intelligens i praksis
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)