PD6010 - Design Thinking and Artificial Intelligence


Examination arrangement

Examination arrangement: Work
Grade: Letter grades

Evaluation Weighting Duration Grade deviation Examination aids
Work 100/100 1 semesters A

Course content

More than ever before, companies and organizations are discovering and exploring the benefits of employing Artificial Intelligence (AI) and autonomous systems. However, many are unable to move from experimenting with AI and autonomous system solutions to obtaining real business value. AI + Design Thinking is a unique interdisciplinary program that aims to create business value by combining the creative craft of design thinking with the technological power of artificial intelligence and autonomous systems. The course focuses on development of user centered AI solution and facilitate interdisciplinary innovation processes. The course will expect you to bring a case related to your own work place, organization or company, and apply a design thinking + AI approach on this case.

Becoming a catalyst of innovation requires mastering three fundamental skills: 1) Being capable of discovering opportunities by viewing challenges and situations with a customer-centric mindset and by framing the "right" problem that needs to be solved, 2). Being able to think differently and interdisciplinary to search for new problems and solutions where AI and autonomy works as an enabling technology, 3). Embracing an experimental attitude to iteratively discover and early testing of what is valuable, feasible and viable.

AI + Design Thinking is based on an AI ecosystem which in addition to the technology includes users, customers, business and organization. The interplay between these elements provides a framework for innovation and value creation in a business perspective.

Elements of AI, autonomy, or similar competence are highly recommended as a basis for the course participation.

The course content is developed in collaboration with leading national and international experts on the new area of fully integrating AI and design thinking. AI + Design Thinking will be delivered as a e-learning course, making it possible to take part independent of where you work.

Learning outcome


As a result of the course, the participant will:

  • Understand the basic functions and possibilities of artificial intelligence and autonomy.
  • Have experience with the mindset, methods and area of application of design thinking
  • Be able to conduct the central components of an insight and ideation phase
  • Understand how end-user needs, technological and economic context impact or are impacted by design thinking
  • Understand how design thinking is best applied to increase the value of a product or service enabled through AI or autonomy
  • Be familiar with the ethical discourse connected with AI and autonomy
  • Know the central principles for critical validation, analysis and presentation of AI data analysis and presentation of AI data 
  • Know how trust can be developed towards AI-systems and autonomous-systems


After completing the course, the participant will be able to:

  • apply design thinking to explore and define the opportunities of AI and autonomous technologies
  • complete end user studies to gain insight into the end-users and stakeholder needs and objectives
  • have the start kit for facilitating design processes for idea generation and concept development bringing tech and people together
  • interpret and analyze AI-data and sensor-data, and transform and present this to customers and other stakeholders
  • suggest possible solutions where AI technologies enable people
  • make first concepts, probes or prototypes to test the appropriateness and opportunities of AI and autonomous systems
  • apply design methods to develop new and innovative areas for the use of AI and autonomous systems
  • visualize and communicate data, concepts and solutions for interests and decision makers

Learning methods and activities

E-learning - with regular digital meetings and coaching sessions

Participants are expected to spend approximately 200 hours on completing the course.

The teaching is based on participants working on projects/themes from their own workplace. This involves allocating time for data collection and collaboration.

This includes:

3 assignments and a final submission, with the first requiring 10-20 hours of work.

2 real-time and mandatory seminars.

Regular guidance from experts from NTNU, Digital Norway, and collaborators based on the chosen theme.

Compulsory assignments

  • Participation workshop 1+2
  • Participation online courses 1+2

Further on evaluation

Deliverables consist of a written project report that can be submitted individually or in groups. If you choose group submission, the same grade will be given to all group members. Lack of attendance/participation in gatherings and teaching can be assessed on the basis of an application to the Department of Design.

Specific conditions

Admission to a programme of study is required:
Externally funded continuing education for the Faculty of Architecture and Design - second degree level (ARDEVU)
Technology Management and Digital Transformation (MTDO)

Required previous knowledge

The admission requirement is twofold:

  1. Completed degree of 180 credits
  2. Minimum of two years of relevant work experience

You must document employment with a certificate from your employer describing the type of job and work tasks, full-time equivalent percentage and duration.

If you do not have a bachelor's degree or equivalent completed education of at least 180 credits, you can request an assessment of prior learning of your admission criteria.

Course materials

Course material will be made available at the start of course and material is shared in connection with the gatherings. The course Elements of AI should be reviewed before the course starts.

More on the course



Version: 1
Credits:  7.5 SP
Study level: Further education, higher degree level


Term no.: 1
Teaching semester:  AUTUMN 2024

Language of instruction: English

Location: Trondheim

Subject area(s)
  • Design Methodology
Contact information
Course coordinator: Lecturer(s):

Department with academic responsibility
Department of Design

Department with administrative responsibility
Section for quality in education and learning environment


Examination arrangement: Work

Term Status code Evaluation Weighting Examination aids Date Time Examination system Room *
Autumn ORD Work 100/100 A INSPERA
Room Building Number of candidates
  • * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.

For more information regarding registration for examination and examination procedures, see "Innsida - Exams"

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