AI Quality – Leading the way to success (Expert Level)

Training Course

Training Course

Are you a professional developing or deploying AI systems? TÜV SÜD’s AI Quality Training course will give you a comprehensive overview of the governance and technical requirements to manage quality. Our AI experts will explain the importance of the organisational setup and enable you to differentiate AI-specific challenges to select matching AI technology for their use cases.

The training will cover imperative requirements from legislation and standards for AI system and AI data management, including a risk assessment process to identify and manage relevant quality measures, essential AI quality controls, and industry best practices. The course provides you with the opportunity to receive a certificate to document your skills development and your organisation’s commitment to meet AI quality requirements.


  • Learning Objectives
    • Identify technology that is governed by AI standards and regulations
    • Manage risks and opportunities in AI
    • Differentiate attack vectors such as adversarial attacks and how to eliminate them
    • 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
    • Implement and manage AI controls
  • Course Agenda
    • The basics: Why do we need dedicated AI Quality Framework?
    • The understanding: How can we define quality of AI?
    • The solution: A comprehensive and compliant AI quality framework
    • The application: Applying AI quality framework in day-to-day operation
  • In-House Course Offering

    TÜV SÜD additionally offers the opportunity to deliver this training as a dedicated in-house course, delivered solely to your organisation to meet your needs and requirements. To receive a quote and find out more information, please contact us at [email protected].



Chief Technology Officer

Martin holds a degree in Computer Science and a PhD in Industrial Design. He has 15+ years of experience in developing technical solutions for both industry and academia. After starting his career at Philips, he established a new research group at A*STAR IHPC and delivered innovation projects in the sectors of Aerospace, Manufacturing, and Retail. At TÜV SÜD, Martin leads strategic research and development initiatives of novel digital testing solutions in the domains of AI, Robotics, and IoT technology.


Executive Engineer, Artificial Intelligence

Over 5 years of experience in all phases of the Software Development Life Cycle (Requirements, Design, Development, Testing, Release / Deployment, Support). This includes 2 years working as a full stack AI Engineer (Data Science, Analytics, Machine Learning and Deep Learning).


Research Engineer, Artificial Intelligence

Rech has recently graduated from the University of Glasgow, Singapore. He previously worked on projects involving adversarial attacks on machine learning systems. Rech will be undertaking research and develop methodology and algorithms for quality assurance in trustworthy AI.


Research Engineer, Artificial Intelligence

Letao holds a bachelor's degree in electrical and electronic engineering from NTU and joined TÜV SÜD as an AI engineer at 2017. He started his PhD in deep learning and interpretability of AI at NTU in 2017. He has experience in data analytics and deep learning and his research focuses on representation learning and generative adversarial network.

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