We’re introducing a new training program: Safe AI — a practical course on building and operating AI systems with a safety mindset, from requirements to evidence and argumentation.
This training is designed for teams who develop, integrate, validate, or approve AI/LLM-based functions in regulated or risk-critical contexts.
What you will learn
- Norms & standards landscape relevant to AI safety and assurance
- Trends in robust LLMs and what actually matters for engineering practice
- AI safety life-cycle: from concept and requirements to validation and change management
- AI architecture from a safety perspective: system boundaries, safety mechanisms, monitoring, fallbacks
- Safety analysis for AI-enabled systems: hazards, failure modes, misuse/abuse cases, and mitigation strategies
- Safety argumentation: how to build credible assurance cases and evidence chains
Hands-on, not theory-only
Every module comes with:
- Demonstrations (live or recorded)
- Real-life examples from engineering projects
- Case studies that walk through decisions, trade-offs, and evidence you’d need in practice
Who it’s for
- Safety engineers, system architects, AI/ML engineers
- Product owners and technical leads
- Verification/validation, quality, compliance, and program managers
Format
- Instructor-led training with structured materials and practical exercises
- Suitable for company-internal sessions or open enrollment (depending on offering)
Training flyer
