BSI has developed a course that explores the importance and impact of implementing robust deep learning systems. We deep dive into the core of the ISO/IEC 24029-1:2021 standard, exploring all its technical parts and actionable contents.
In this course, we will introduce the concept of robustness in the context of deep learning systems, by exploring the potential dangers of non-robust neural networks and proposing a workflow for identifying and assessing robustness issues, following ISO/IEC 24029-1:2021.
How will I benefit?
This course will help you:
- Understand the meaning of robustness in AI systems - a key concept in the forthcoming EU AI regulation
- Spot where and how robustness concerns may arise
- Understand the different kinds of robustness issues 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
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
What's included?
- This is an online, interactive eLearning course.
- You’ll have access to the course for 12 months.
On completion, you'll be awarded an internationally recognized BSI Training Academy certificate
