Artificial Intelligence

Artificial Intelligence Quality Trainings

A comprehensive set of practical trainings to master AI & Data quality

A comprehensive set of practical trainings to master AI & Data quality

ESSENTIAL AI QUALITY skills

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

 

TÜV SÜD has developed a comprehensive training offer catered to executives, AI practitioners and AI experts, as well as quality managers. Our training modules provides you the skills to govern AI quality – a prerequisite to successfully develop AI at scale. Our AI experts will guide you through existing and upcoming AI standards, regulations, benchmarks, and industry best practices.

 

OUR AI QUALITY TRAINING MODULES

“The TÜV SÜD Seminar on AI Quality Management is a must for responsible AI developers building the solutions of a digital tomorrow. The seminar is comprehensive and it gives an excellent overview of the breadth of AI Quality. Hands-on examples, carefully selected references, and good seminar documentation provide a north star for our own developments.”

- Dr. Christoph Hofmann, Head of Cooperative Safety Solutions, SICK AG

WHY CHOOSE TÜV SÜD AI training

 

Our trainers are AI experts. We are not merely keeping abreast with the latest algorithms, upcoming standards and regulations in AI, but are actively shaping the standardisation and regulatory landscape. We provide thought leadership by contributing to key committees and publishing academic, peer-reviewed papers. Our trainings consolidate decades of history in assessing and managing technical systems quality, combined with our close-to-market AI quality audits and advisory services.

With TÜV SÜD, you can learn to:

  • differentiate technology that is governed by AI standards and regulations
  • manage risks and opportunities in AI
  • identify 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

Throughout the training, our experts will illustrate the concepts with practical real-world use cases.

 

OUR TRAINING PORTFOLIO


EXPLORE

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AI Quality Readiness Analysis

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