A practical guide to gain the required knowledge to master AI quality

A practical guide to gain the required knowledge to master AI quality


  • Globally recognised Training Certificate for AI Quality
  • Access to our community of experts for strategic guidance and continuous improvement
  • Understand how to successfully apply a quality management system for AI
  • Choose from the 2 training modules, each specially developed for Executives and Experts to equip them with the relevant skills to effectively perform their roles in their organisations
  • Learning through case studies & exercises


Benefitting from AI requires more than just implementing the technology. Organisations need to understand AI standards and regulations, recognise and predict the impact of AI on the business and manage the quality accordingly.

TÜV SÜD has developed AI Quality training modules catered to Executives and Experts that equip organisations with skills to govern AI quality – a prerequisite to develop and adopt AI at scale. Our AI experts will guide you through quality requirements that include existing and upcoming AI standards, regulations, benchmarks, and industry best practices.


  • AI Quality Training – Roles and responsibilities for leaders (Executive – 4h)

    In this training course, organisational leaders will comprehend their roles, responsibilities and liabilities and will be enabled to plan their AI development and adoption strategy.

    1. Motivation
      • Introduction to AI and the need for AI quality
      • Current and upcoming regulation of AI 
      • Roles, responsibilities and liabilities
    2. AI quality framework to establish trust in AI and scale AI applications
      • Compliance of AI systems and services
      • Readiness of organisations as developer and adopter
      • Performance metrics and industry best practices
    3. Path towards AI quality
      • Skills and responsibilities - Train your AI leads and assign roles to implement AI quality
      • Assess your organisation’s AI quality readiness
      • Stepwise implementation of AI quality framework
  • AI Quality Training – A practical guide to gain the required knowledge to master AI quality (Expert – 2 days)

    In this TÜV SÜD’s AI Quality Training course for professionals, our AI experts will reveal the importance of the organisational setup and enable participants to differentiate AI-specific challenges and select the respective matching AI technology for their use cases. The training will cover imperative requirements for AI system and AI data management, a risk assessment process to identify and manage relevant quality measures, essential AI quality controls, and industry best practices. The course offers participants the opportunity to receive a certificate to document skill development and organisation’s commitment to meet AI quality requirements.

    1. The basics: Why do we need dedicated AI Quality Framework
      • Introduction to AI quality
      • AI technologies: Strengths and weaknesses of core algorithms and how to choose the right one
      • AI challenges and failures
      • AI reference architecture: How to describe an AI system and its boundaries
      • Case study
    2. The understanding: How can we define quality of AI?
      • Concepts of AI quality
      • AI stakeholders
      • AI system quality model: safety, security, legal, ethics, performance
      • AI process model
      • AI governance
      • AI risk assessment
      • Case study
    3. The solution: A comprehensive and compliant AI quality framework
      • AI system life cycle
      • AI data quality model
      • AI data life cycle
      • AI standards AI regulation
      • Case study
    4. The application: Applying AI quality framework in day-to-day operation
      • AI quality Controls
      • AI explicability
      • AI robustness
      • AI cybersecurity
      • AI testing
      • Case study



AI Quality Training (Expert): 2 Days Instructor-led training


The AI Quality Executive course is suitable for organisational leaders who need to know how to identify and manage individual and organisational risks associated with AI technology, the impact of AI regulations and standards, and AI performance metrics and industry best practices, enabling them to plan their AI development and adoption strategy.

The AI Quality Expert course is ideal for professionals developing or deploying AI systems or products provides an introduction and comprehensive overview of the governance and technical requirements to manage quality of AI systems.


  • Learn how to differentiate technology that is governed by AI standards and regulations
  • Be well-equipped to manage risks and opportunities in AI
  • Know how to identify attack vectors such as adversarial attacks and how to eliminate them
  • Be able to define quality criteria such as robustness, accuracy, reliability, explicability and methods how to control them
  • Classify AI roles, responsibilities, and liabilities for organisations and individuals 
  • Specify key components of AI governance
  • Learning through case studies & exercises


Possess familiarity with basic machine learning concepts (high-level)


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