Course 1 Complete — What You've Built
That's the security course done. Before you move on, take stock of what you've actually built.
What You Now Know
- ◆The full AI attack surface across the model lifecycle — data, training, deployment, integration
- ◆Why traditional cybersecurity tools cannot detect AI-specific threats
- ◆The four adversarial attack types and the defences for each
- ◆How training data poisoning works and how to protect your training pipelines
- ◆The risk of model memorisation and its GDPR implications
- ◆How to assess and manage your AI supply chain
- ◆What prompt injection and jailbreaking are and how to build LLM deployments that resist them
- ◆How to detect, classify, and respond to AI security incidents
- ◆The five pillars of AI security governance
If you're ready to go further, Course 2 covers the regulatory and governance side — the EU AI Act, GDPR, compliance frameworks, and how to build an AI governance programme that satisfies both regulators and your board.
Security exposure grows fast as you move up the AI‑Native Roadmap — a Level 1 data tool has a small attack surface; a Level 3 or 4 multi‑agent system has a large one. This course is the security foundation that makes moving up a level safe. It's also exactly the ground U4RIA covers in an AI Trust Exposure Review — a structured assessment of how exposed your AI deployments really are.
Before moving to Course 2, take 20 minutes to build your AI system inventory. Even a rough first version — a list of every AI tool your organisation uses, who owns it, and what data it touches — will transform your ability to apply everything in this course.
