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Owning an AI System Course & Certification
Intermediate
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4.7
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97% Recommended
Updated 2026
4 hours
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Each course includes:
Free eBook
Get our exclusive eBook with every purchase – a practical companion guide to owning an AI system, covering system ownership, lifecycle management, risk assessment, validation, deployment, monitoring, change control, documentation and retirement within regulated environments, yours to keep forever.
CPD Points
Gain Continuing Professional Development (CPD) Points while building practical knowledge of owning and managing AI systems throughout their lifecycle. This course supports ongoing professional development by helping learners understand AI system ownership, governance responsibilities, risk management, validation, deployment, performance monitoring, change control and lifecycle documentation across regulated life-sciences and healthcare organisations.
Certification
Receive a personal certificate to demonstrate your knowledge of AI system ownership and lifecycle management upon successful completion of the course.
Affordable
You get excellent value through our cost-effective prices while gaining practical knowledge of AI system ownership, governance and lifecycle management in regulated environments. We can also offer group discounts on larger purchases.
Flexibility
The course saves you time through the convenience of online availability. This allows you to complete the interactive training on AI system ownership and lifecycle management at your own pace, wherever and whenever it suits you.
Keep Up to Date
You will stay up to date with key developments in AI system ownership and lifecycle management, including the EU AI Act, GDPR/UK GDPR considerations, AI governance expectations, risk management, validation, human oversight, performance monitoring and change control within regulated life-sciences environments. Our courses are continually monitored, reviewed and updated to reflect current regulatory, compliance and industry developments.
Learn from Industry Experts
The content has been developed by AI governance, quality, regulatory and compliance practitioners to help learners understand the principles of AI system ownership, lifecycle management and governance, and apply them within regulated life-sciences environments.
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About
Owning an AI System training provides practical knowledge of AI system ownership and lifecycle management in regulated life-sciences environments.
Learners explore intended use, governance, accountability, risk assessment, validation, deployment, human oversight, performance monitoring, change control and retirement.
The course covers supplier management, documentation, traceability, data integrity, privacy, security, fairness and incident management.
Practical examples demonstrate how to maintain effective controls and ensure AI systems remain fit for their intended use.
Learners also explore the relevance of GxP, data-protection requirements, recognised standards and the EU AI Act.
Upon successful completion, learners receive a certificate demonstrating their knowledge of AI system ownership and lifecycle management.
Who Should Enrol?
- AI System Owners, Governance, Quality, Regulatory and Compliance Professionals
- Pharmaceutical, Biotechnology, Medical Device and Life Sciences Professionals
- GxP, Validation, IT, Digital Transformation and AI Professionals
- Data, Privacy, Security, Risk Management and Project Management Professionals
What you will learn
Understand the principles of AI system ownership and lifecycle management in regulated life-sciences environments, including intended-use definition, accountability, governance responsibilities, provider and deployer roles, and regulatory expectations.
Learn how to manage AI systems from initial selection and assessment through validation, deployment, performance monitoring, change control and retirement, while considering safety, fairness, privacy, security, data integrity and human oversight.
Develop practical knowledge of AI risk assessment, lifecycle documentation, traceability, supplier management, incident handling and ongoing performance evaluation to help ensure AI systems remain fit for their intended use.
Gain an understanding of how AI lifecycle responsibilities interact with GxP requirements, data-protection obligations, recognised standards and the EU AI Act to support responsible, compliant and inspection-ready AI system management.
Course Syllabus
- A Defence You Can Evidence, Not a Human You Can Name
- The order is the order a system is actually taken on
- Melbrigg Group - case study
- Every instrument on these screens carries its status
- The artefact everything else is measured against
- Purpose, and the input sample space
- Edge cases, failure modes and bias
- Who signs it, and the date the signature has to precede
- Context of use and credibility: the medicines-side words
- Classification as a record, and purpose across the whole life
- The package a model actually needs
- Acceptance criteria before testing
- The benchmark: the process you would replace
- Test data nobody touched
- The hold-out set is spent the moment you look at it
- Evaluate the system that will actually run
- Two tests, one change, one file
- The device-law test, and a guidance written before the problem
- The AI Act test, and the route that needs writing down first
- The mature comparator, and what travels
- The United Kingdom proposal, and a sheet you can defend
- Same technique, opposite answers - and the file you hand over
- The obligation is dense. The methodology was not located.
- The obligations that do bite, and where each one sits
- Device-law surveillance, and a guidance that never says AI
- Choosing a measure, setting a level, defending the choice
- Oversight decay, the override rate, and re-qualification
- From a monitored level to a change that may proceed
- What is settled, what is draft, and what was reopened
- Guardrails, and what the measurement actually shows
- Close human supervision, and the step that records it
- The supplier file, and what you demand in writing
- The production surface: what an authority actually reads
- The assessor, the auditor, and the one published finding
- Taking ownership of a system, in the order it happens
- How you defend a level no scan of the record located
- What to do when you get back to your own system
- Course completion
- 📘 Bonus: Owning an AI System eBook (Free with purchase)
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