Robustness for neural networks – ISO/IEC 24029-1:2021 introduction on-demand training course

Duration 2.5 hours

Available to book: On-demand elearning PHP5000 See all dates and book

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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.

How will I benefit?

This course will help you:

Build a toolset of methods that can help identifying robustness issues
Understand the different types of data perturbations, and their use in the creation robustness test data sets
Design workflows to detect and address robustness concerns
Take steps to ensure that the assessment of robustness 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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