Robustness for neural networks – ISO/IEC 24029-1:2021 introduction - eLearning

Stufe Grundlagen Dauer 2,5 Stunden

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Assessing robustness of AI systems is a crucial part of their development and deployment. Here at BSI, we have developed a course that explores in depth the importance and impact of implementing robust deep learning systems, following the Standard ISO/IEC 24029-1:2021. We deep dive into the core of the standard, exploring all its technical parts and the corresponding actionable contents.

On-demand - training that’s even more flexible

BSI’s on-demand courses are market-leading and available 24/7. Developed by top subject matter experts, they contain the same high-quality content you will find in our tutor-led training, but with the added benefit of being able to learn at your own pace and at any time.

How will I benefit?

This course will help you:

Build a toolset of methods that can help identify robustness issues
Understand the different types of data perturbations, and their use in the creation of robustness test data sets
Design workflows to detect and address robustness concerns
Take steps to ensure that robustness assessment is part of the development and deployment of AI systems involving neural networks

Upon completion of this course, you will be able to:
- Apply the methods provided by the standard to detect robustness issues arising in the development and deployment of a deep learning system
- Describe the main principles behind data perturbation and abstract interpretation
- Construct protocols to assess robustness of a neural network
- Data Scientists
- Data Analysts
- Data Engineers
- Machine Learning Engineers
- AI architects
On completion, you'll be awarded an internationally recognized BSI Training Academy certificate

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