Trustworthy Artificial Intelligence

  • Credits 2.5  credits
  • Education level Second cycle
  • Study location Distance with no obligatory meetings
  • Course code DVA507
  • Main area Computer Science

Would you like to learn about trustworthy artificial intelligence? This course provides you with the necessary knowledge to critically evaluate existing AI methods, techniques, and algorithms. We focus on reliability, explainability, transparency, fairness, and trust in AI systems.

About the course

AI systems are increasingly being integrated into various industrial processes, including manufacturing, logistics, and autonomous vehicles. Trustworthy AI ensures that these systems operate reliably, reducing the risk of accidents or costly errors.

Trustworthy AI helps companies comply with ethical standards and legal regulations. It ensures that AI systems do not discriminate against certain groups, violate privacy rights, or engage in other unethical behaviors. Trustworthy AI System course can support in the development of more advanced AI technologies, fostering research collaboration, and attracting talent.

You will learn

  • to describe and understand the fundamentals of trustworthy AI,
  • apply XAI methods and algorithms
  • understand the measures of fair ML


Below you find the entry requirements for the course. If you do not fulfill the requirements, you can get your eligibility evaluated based on knowledge acquired in other ways, such as work experience, other studies etcetera. Read more in Application information below.

Occasions for this course

Autumn semester 2024

  • Autumn semester 2024


    2.5 credits


    2024-11-11 - 2024-12-29 (part time 25%)

    Education level

    Second cycle

    Course type

    Freestanding course

    Application code




    Study location

    Independent of location

    Teaching form

    Distance learning
    Number of mandatory occasions including examination: 0
    Number of other physical occasions: 0

    Course syllabus & literature

    See course plan and literature list (DVA507)

    Specific requirements

    90 credits of which at least 60 credits in Computer Science or equivalent, including 15 credits in programming as well as 2,5 credits in basic probability theory and 2,5 credits in linear algebra, or equivalent.  In addition, Swedish course B/Swedish course 3 and English course A/English course 6 are required. For courses given entirely in English exemption is made from the requirement in Swedish course B/Swedish course 3. 


    University credits

Questions about the course?

If you have any questions about the course, please contact the Course Coordinator.


Shahina Begum