Recent advances in Machine Learning (ML) and Artificial Intelligence (AI) are leading to increased ML and AI deployment in commercial and personal applications.
ML and AI deployment in safety critical applications carries increased risk of adverse events. In this course we will review important topics for ML and AI being used in safety critical tasks, including:
- Introduction to Machine Learning: challenges for safety
- Functional Safety Standards guidance on ML and AI
- Typical ML paradigms for safety applications
- Concepts for safe ML data analysis
- ML statistical analysis for safety applications
- Synthetic data and generated data: risks and opportunities
The course will include a mix of theory-based sessions and practical (coding) sessions using Python.