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The complete, ordered path from AI-threat basics to attacking and defending real AI systems — adversarial ML, LLM red-teaming and securing the model supply chain.
Become the person who can break an AI system before an attacker does — and then harden it, across data, model and deployment.
From the AI threat landscape to hands-on red-teaming and a practitioner credential.
7 milestones, each anchored to one course. Follow them in order — every step is built on the one before.
Start with the landscape — poisoning, evasion, extraction, prompt injection — in plain language.
Ground your security work in why AI systems fail and where governance and security meet.
Protect the whole lifecycle — training data, model artefacts and deployment — from tampering and theft.
Learn the defensive patterns for LLM apps — input handling, guardrails and monitoring.
The core skill. Probe, break and document weaknesses in a real LLM application.
Bring attack and defence together on a full system and produce a hardening report.
Consolidate into a certification-ready AI security practitioner finish.
You don't have to buy these 7 courses one by one. We've packaged the complete roadmap into a single bundle, so the entire journey comes at one discounted price.
All 7 courses across the path, plus the capstone project — everything you need to finish, in one purchase.
Or unlock this bundle and every other roadmap with an all-access membership.
Basic familiarity with how models work helps, but the path starts with fundamentals and builds the security angle from there.
About 15 weeks part-time, self-paced.
Yes — several milestones are labs and a full red-teaming project you can show in a portfolio.
Yes — all are in the catalog. The bundle is cheaper and adds the capstone.