KIUA2900 Bachelor’s thesis

    • Course code
      KIUA2900
    • Number of credits
      30
    • Teaching semester
      2027 Spring
    • Language of instruction
      Norwegian/English
    • Campus
      Hamar
    • Required prerequisite knowledge

      All courses from the first and second academic year passed, including elective courses. A total of 120 credits.

Course content

The bachelor’s examination is the final component in AI: the development and application step in which students will demonstrate extensive and advanced knowledge of the use of AI and ML acquired from previous courses in the programme. Students will be able to combine all academic knowledge and skills learned on the programme to complete all tasks for the bachelor’s thesis. The bachelor project may be an individual or collaborative project linked to the specialism chosen by the student.

Learning Outcome

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

Knowledge

The student will have

  • knowledge of presentation techniques
  • in-depth knowledge of value creation in AI and ML projects
  • knowledge of implementing projects within the fields covered by the programme
  • knowledge of production relating to AI
  • knowledge of critical thinking, communication and problem-solving linked to technological and interactive products
  • extensive knowledge of their own area of specialisation and insights into related fields
  • knowledge of solving problems presented in a project
Skills

The student will be able to

  • assess workload in relation to quality
  • deliver different types of presentations to promote a project
  • develop the production process in an interdisciplinary project
  • master and apply relevant tools, methods and theory for their project
  • understand technological processes from idea to final product
  • apply academic knowledge and results from research and development work that are of relevance to the problem
  • master critical thinking, source criticism, logic and communication in problem-solving
  • reflect on and evaluate their own work in the project and development process
  • reflect on their own professional practices and adjust these under supervision
General competence

The student will be able to

  • plan and execute projects that extend over time in line with ethical requirements and guidelines
  • master Norwegian or English, orally and in writing, and can use language in a qualified manner in a professional context and in academic work
  • inspire and accommodate entrepreneurship, new thinking and innovation
  • communicate key subject matter, orally, visually and in writing
  • utilise different types of digital tools in an effective and planned manner
  • think strategically in relation to self-promotion, marketing and business development
  • develop ideas and concepts for AI-related projects
  • participate in discussions relating to different aspects of a project
Teaching and working methods

The problem and research question will be drawn up in consultation with the academic supervisor (from different faculties at the University) within three weeks of the sixth semester starting, but all projects must be pre-approved by the panel of nominated members from the Faculty before they can be carried out. In cases where a group’s proposed project cannot be approved, the group may be allocated an internal project.

Required coursework
  • presentation and submission of 1 assignment
  • participation in 2-3 group seminars
  • participation in 3-5 academic supervision meetings

Coursework requirements will be specified in further detail in the course curriculum.

Compulsory coursework requirements that have been passed are valid for 12 months only. Students wishing to take examinations after 12 months must pass the compulsory coursework requirements again in connection with the next scheduled delivery of the course.

Assessments
Form of assessmentGrading scaleGroupingDuration of assessmentSupport materialsProportionComment
Written examination with an adjusting oral examination
ECTS - A-F
Group/Individual
100
Form of assessment
  • individual/group-based project consisting of product/algorithm/solution and reflection note
  • oral group presentation that can affect the grade of the project

When taking part in group assignments, all participants in the group will be jointly responsible for all content of the assignment/work.

The assignment is assessed using a grading scale from A-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:

  • Syllabus 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: 
Bacheloroppgave
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)