AI Coordinator Training Course
Competently design AI, manage risks, accompany implementation – with TÜV certificate
Our two-day AI Coordinator training course with exam enables you to identify areas of application of AI in the company, analyse risks and opportunities, and support the implementation of AI projects. The live online coursefocuses on all aspects of AI quality through an application-oriented mix of theoretical expertise and practical exercises.
✔ Learn how to manage quality and risk at all stages of the AI life cycle
✔ Understand how to identify and avoid potential mistakes in AI adoption
✔ Become familiar with the current status of the legal and normative requirements
✔ Discover how to plan an AI quality management system with a roadmap to launch
Artificial intelligence is now a core technology in many organisations, creating the need for qualified specialists. As a certified AI Coordinator, you act as the operational link between AI strategy and practical implementation, turning concepts into projects that drive digital transformation.
This foundation-level AI coordinator training course enables you to identify AI areas of application in your organisation, analyse risks and opportunities, ensure compliance with legal and regulatory requirements, and guide successful project delivery. You will gain practical tools to evaluate your organisation’s AI maturity and support the safe, effective deployment of AI systems.
AI Coordinators are valuable both within organisations and as external consultants. Your certification will help you progress within your careers asyou’ll be able to complete further training with our AI Officer training course.
We start with an introduction to why AI quality is essential for organisations, exploring what artificial intelligencemeans for businesses, the challenges of adoption, and the potential risks associated with AI applications. Then, you’ll learn about the risk-based framework for AI quality, including the six key pillars: security, cybersecurity, compliance, ethics, performance, and sustainability.
Next, we cover risk assessment and AI Quality Maturity Analysis to help you evaluate your organisation’s AI readiness. You’ll gain an overview of ISO/IEC 42001, understand the importanceof organisational context, and explore compliance requirements, legal standards, and ongoing regulatory activities. We then move on to developing anAI strategy, identifying required skills and competencies, and reviewing a practical example of a company’s maturity profile.
You’ll then study AI systems including the AI reference architecture covering data quality, AI models, and AI training, as well as integration and monitoring processes such as testing and control. This section includes an application example of an AI system maturity analysis.
The following part focuses on AI processes and the AI and data life cycle, addressing each phase and its quality aspects. You’ll learn how to manage risks across the entire life cycle and apply methods for validation, verification, and explainability. Cybersecurity topics such as AI security, potential attacks, and defence mechanisms are also covered, supported by an application example of a maturity profile of AI processes.
In the final part of our AI Coordinator training course, you’ll learn how to plan an AI quality management system and create a roadmap for implementation.
By the end of this two-day foundation-level course, you should be prepared to take the AI Coordinator certification exam, ready to identify AI opportunities, assess risks, ensure compliance, and support successful AI integration within your organisation.
Train with the experts
You’ll be taught by leading industry experts with specialist knowledge of your sector. For over 35 years, our global team of more than 2,500 instructors, has been bringing real-world experience to the classroom. Course content is regularly updated to reflect changes in legislation and ensure relevance. Discover more on our why train with us page.
Training five or more people?
Find out if an in-house course is a more cost-effective, efficient way of learning. Contact the In-House Training team.
Please note this course is run by TÜV SÜD Akademie GmbH.
- Managing directors and IT managers specialising in the strategic integration of AIwithin their organisations needing to expand their knowledge and skills in overseeing AI adoption and ensuring alignment with business objectives
- AI and software engineers developing and deploying AI systems who need to understand the impact of AI quality, compliance, and performance on reliablesystem outcomes
- Data analysts and software developers required to know how to apply AI responsibly and effectively by developing knowledge and skills in data quality, model validation, and life cycle management
- Compliance and quality managers involved in governance and assurance of AI systems who want to understand the impact of evolving regulations, standards,and ethical requirements on AI implementation
- Consultants and AI subject matter experts supervising AI projects who need to learn more about assessing AI maturity, managing risks, and ensuring adherence to quality principles
- Gain evidence of your AI expertise with a TÜVcertificate
- Your company has the opportunity to demonstrate the responsible use of AI by employing competent experts
Introduction: Why is AI quality so important?
- Definition and importance of AI for companies
- Challenges of AI adoption
- Risks of AI applications
The risk-based framework for AI quality
- The 6 pillars of AI quality: security, cybersecurity, compliance, ethics, performance, sustainability
- Risk assessment
- AI Quality Maturity Analysis
AI readiness of the organisation
- ISO/IEC 42001 overview
- Expectations of the context
- Compliance: Legal requirements, standards and ongoing regulatory activities
- AI strategy
- Required skills and competencies
- Application example: Maturity profile of a company
AI Systems
- AI reference architecture: Core areas (data quality, AI models, AI training), Integration (execution, control flow), Monitoring (testing and control)
- Infrastructure
- Application example: Maturity analysis of an AI system
AI Processes
- AI & data life cycle – phases and quality
- Interaction between
- AI and data life cycle
- Risk management over the entire life cycle
- Validation and verification: Methods for AI explainability
- Cybersecurity – AI security, attacks and defence
- Application example: Maturity profile of AI processes
Planning an AI quality management system
- Roadmap to launch
- Course delivered by one of TÜV SÜD's leading industry experts
- Small class sizes for a more engaging and personalised learning experience
- Receive globally recognised TÜV SÜD certificate upon completion
TÜV SÜD is trusted by over 16,000 companies and thousands of learners worldwide, reflecting our commitment to delivering quality training.
None, but basic knowledge of common machine learning algorithms is recommended
What is the AI Coordinator Training Course?
The AI CoordinatorTraining Course trains professionals to manage AI quality, risk, and compliance. This two-day course covers legal standards, AI lifecycle frameworks, and risk-based planning. Participants gain practical expertise andreceive a certificate demonstrating their ability to guide safe and effective AI implementation. Why AIquality and governance matter.
What is the goal of the AI Coordinator Training Course?
The course equips professionals to manage AI quality and risk across all lifecycle stages. Participants learn to identify AI opportunities, ensure compliance with emerging standards, and lead responsible AI implementation within their organisations.
How long is the AI Coordinator Training Course?
The course runs for two intensive days, combining theoretical knowledge with hands-on exercises, practical examples, and a certification exam at the end.
What prior knowledge do I need?
No formal prerequisites are required. However, basic familiarity with machine learning concepts or data-driven technologies is beneficial for understanding the course material more effectively.
What types of organisations does TÜV SÜD Academy train in the AICoordinator course?
TÜV SÜD Academy trains professionals from a wide range of industries, including technology, manufacturing, automotive, healthcare, finance, and public research. Our clients trust TÜV SÜD to build practical AI competence and demonstrate responsible, compliant use of AI across their operations.
How is the course structured?
It consists of 9 sections and 10 modules covering AI quality fundamentals, risk assessment, ISO/IEC 42001, data and process maturity, explainability, and cybersecurity, culminating in a roadmap for AI quality management.
What certification will I receive?
Upon successful completion of the exam, you will receive the “AI Coordinator – TÜV” certificate, demonstrating competence in AI quality management and compliance under TÜV SÜD standards.
How does this training support career growth?
Certified AI Coordinators are in high demand for roles involving AI project management, compliance, and governance. Thecertification also qualifies you to progress to the advanced AI Officer –TÜV programme.
Can this course be delivered in-house for my team?
Yes. TÜV SÜD Academy offers custom in-house delivery for teams of five or more, allowing organisations to tailor content to specific AI applications and governance needs.