KIUA2005 Development II

    • Course code
      KIUA2005
    • Number of credits
      15
    • Teaching semester
      2027 Autumn
    • Language of instruction and examination
      Norwegian/English
    • Campus
      Hamar
    • Required prerequisite knowledge

      Recommended: KIUA2004 Development I

Course content

This course provides a comprehensive introduction to the development of advanced AI and ML technologies. This course will also guide students on the gathering of requirements from various domains. Students will be taught how to use these requirements to develop such AI and ML technologies. Through this course, students will also learn about integration readiness of such AI and ML technologies in relation to different domains. Students will continue to develop general skills in project planning and knowledge sharing as part of this course.

Learning outcome

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

Knowledge

Students have:

  • Knowledge about the development of advanced AI and ML technologies
  • Knowledge about requirements from different domains that can guide the development of such AI and ML technologies
  • Knowledge about embedding such developed AI and ML technology with integration readiness into various domains
Skills

Students can:

  • Understand and develop advanced AI and ML technologies
  • Systematically gather requirements from different domains to develop such AI and ML technologies
  • Develop such AI and ML technologies in terms of integration readiness in relation to different domains
General competence

Students can:

  • Develop advanced AI and ML technologies for real-world problems
  • Develop advanced integration-ready AI and ML technologies and tools in relation to 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
Course name in Norwegian Bokmål: 
Utvikling II
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
Third-year courses, level III (300-LN)