Trustworthy AI and Governance
Halmstad University
Ortsoberoende
Start date:
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Pace of study: 17 %
Published education catalogue
Education information from the published source. The education record and its time-bound offerings are kept separate.
Code: DT8068
### Who is this course for? This course provides a practical introduction to AI regulation and the development of trustworthy AI systems. It is intended for professionals with a background in AI, data science, law, compliance, or management, who want to understand how to design, deploy, and govern AI systems in line with the EU AI Act and principles of trustworthy AI. ### What will you learn from this course? Students will learn about the legal and regulatory framework for AI, including the classification of AI systems by risk and enforcement timelines under the EU AI Act. They will explore key principles of trustworthy AI, such as fairness, transparency, explainability, and accountability, and gain skills in designing compliance roadmaps, performing AI risk assessments, and implementing governance measures across AI lifecycles. The course also covers organizational readiness, participatory design, and strategies for embedding trustworthiness in AI development. ### What is the format for this course? Instruction type: Asynchronous online modules + optional live Q&As/workshops. Methods: Case studies, expert videos, scenario-based and co-design learning. Examination: Quizzes and practical project (e.g., AI risk analysis or compliance strategy).
Degree of Bachelor or Degree of Bachelor of Science in Engineering. The degree must be equivalent to a Swedish kandidatexamen or Swedish högskoleingenjörsexamen and must have been awarded from an internationally recognised university. English 6 or English level 2. Exemption of the requirement in Swedish is granted for those with foreign grades.
Each offering has its own dates and conditions. Closed offerings are retained as history and do not mean that a new application is open.
Halmstad University
Ortsoberoende
Start date:
End date:
Pace of study: 17 %
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Published: .
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Last changed according to the source: 2026-07-13T10:29:55