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KIUA2005 AI application design

    • Course code
      KIUA2005
    • Number of credits
      10
    • Teaching semester
      2026 Autumn
    • Language of instruction
      Norwegian/English
    • Campus
      Hamar
    • Required prerequisite knowledge

      Recommended: KIUA2004 Deep Reinforcement Learning & Neural Networks

Course content

The course will provide students with an extensive understanding of the capabilities and limitations of AI and machine learning technologies, with a focus on their applications within product and service design. The course will equip students with knowledge, skills and a strong ethical foundation to develop AI-driven solutions that meet user needs, comply with ethical standards and contribute to innovation in the field. Students will also acquire skills in designing recommendation systems and conducting user surveys in order to develop intuitive, user-centred AI interfaces. The course encourages creative problem-solving, promotes ethical responsibility in design, improves collaboration and communication and emphasises critical thinking. Overall, the course will give students the ability to design innovative, user-centric AI solutions while maintaining ethical standards and promoting collaboration and critical thinking.

Learning Outcome

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

Knowledge

The student will have

  • knowledge and a comprehensive understanding of the possibilities and limitations of AI and machine learning technologies and different types of AI algorithms, such as recommendation systems and chatbots and their applications in product and service design
  • knowledge of ethical challenges and considerations specific to AI design and the importance of fairness, transparency, accountability and privacy in AI-driven products and services
  • knowledge of user-centred design principles and methods, how to identify user needs, preferences and pain points, with an understanding of the importance of designing AI systems in line with user expectations and how to improve the user experience
Skills

The student will be able to

  • design recommendation systems and algorithms that match user needs to relevant products or services and utilise AI algorithms for collaborative filtering and content-based filtering to provide personal recommendations
  • conduct user research, including interviews and usability testing, to understand user needs and preferences and design intuitive user interfaces and interactions that incorporate AI capabilities
  • apply service design principles to improve the delivery of AI-driven services in the design and development of AI-driven chatbots, virtual assistants and voice interfaces to improve customer support and optimise service processes
General competence

The student will be able to

  • implement creative problem-solving processes to design new products and services that utilise AI and machine learning and encourage innovative thinking and exploration of new approaches in order to meet user needs and challenges
  • promote an ethical mindset and develop responsible AI design with regard to the ethical implications of design choices and develop AI-driven solutions in line with societal values in order to safeguard user privacy
  • effectively collaborate with team members, stakeholders and end users to design and communicate AI-driven solutions
  • apply critical thinking in order to evaluate the impact and efficiency of AI-driven design solutions, evaluate usability and user satisfaction of AI systems and iterate the design based on user feedback
Teaching and working methods

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

Required coursework
  • 1 group assignment
  • 1 individual assignment

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 assignment
ECTS - A-F
Individual
100
Form of assessment
  • One individual project-based assignment

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:

  • 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: 
Design av KI-applikasjoner
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)