Assessing robustness of AI systems is a crucial part of their development and deployment. Here at BSI, we have developed a short course that explores the main principles and the importance of implementing robust deep learning systems, as outlined in ISO/IEC 24029-1:2021.
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.
The aim of this course is to give awareness of the concept of robustness in the context of deep learning systems, by exploring the dangers that can affect non-robust neural networks and proposing a workflow to detect and assess robustness issues, following ISO/IEC 24029-1:2021.
How will I benefit?
This course will help you:
- Gain awareness of the meaning of robustness in the context of AI systems, which is a key concept in the forthcoming EU AI regulation
- Spot where and how robustness concerns may arise
- Understand the different kinds of robustness issues that one can face in the development and deployment of deep learning systems
What will I learn?
Upon completion of this course, you will be able to:
- Explain what robustness of an AI system is
- Recognize the different kinds of robustness issues that one can face in the development and deployment of deep learning systems
Who should attend?
- AI Managers
- Data Governance Managers
- Data Scientists
- Data Analysts
- Data Engineers
- Machine Learning Engineers
- AI architects