Delivery format
In person
Course overview
On the Evaluation and Governance of AI in Healthcare course you will learn how to appraise existing evidence about AI health technologies and how to generate local evidence to support decision-making in a specific setting. You will also gain an understanding of the different forms of risk that AI health technologies pose for healthcare providers and the principles and practicalities that influence how those risks are managed.
Best practices in these key areas are emerging, with limited capabilities across many UK and global healthcare providers. Because of the interdisciplinarity and novelty of the challenges posed by AI governance and evaluation in healthcare, this course is accessible for a wide range of applicants. This practice-oriented module is grounded in the faculty’s recent or active research in the UK, US and elsewhere. You will develop competencies that enable you to bring organisations up to date to efficiently deliver safe, effective and fair AI-enabled healthcare.
Course delivery
On completion of the course attendees will be able to:
- Show understanding of the organisational structures and capabilities required to facilitate effective AI governance in healthcare
- Show understanding of the core principles of cyber security, interoperability and clinical risk management relating to clinical AI
- Evaluate peer-reviewed evidence of clinical AI performance across the translational pathway
- Evaluate local risks and propose mitigations for an AI-enabled healthcare pathway
Dates of the course
Monday 2 March 2026 - Friday 6 March 2026
On completion of the course attendees will receive a certificate of completion.
Teaching staff
Dr Jeffry Hogg
Clinical AI Implementation
School of Infection, Inflammation and Immunology
Staff profile for Dr Jeffry Hogg, Honorary Clinical Research Associate, College of Medicine and Health, University Â鶹¾«Ñ¡.
Alastair Denniston
Chair of Regulatory Science and Innovation
Department of Health Sciences
Alastair Denniston is Professor of Regulatory Science and Innovation at the University Â鶹¾«Ñ¡. He is a leader in the field of Artificial Intelligence (AI) and Digital Health Technologies.
Entry requirements
This course is suitable for recent graduates from healthcare, management, technical or innovation degree programmes. The course is also suitable for mid-career applicants with practical, policy or research roles in healthcare or medtech.
Fees and scholarships
£1011.11
Application process
Whilst places remain available, applications can be made through the link to the online shop until 9 February 2026. When the course is fully booked, prospective applicants will be added to a waiting list and informed of any additional availability or future courses.
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