Map the AI Risk You're Already Carrying — Live
Join Nahid Farady, PhD (Principal Tech Lead, AI Security & Privacy · Microsoft) for a free live session.
Nahid Farady, PhD
Principal Tech Lead, AI Security & Privacy · Microsoft
⭐ 4.9 / 5
Your AI systems have undocumented risk. Here's how to find it.
Most teams shipping LLM apps, RAG pipelines, and AI agents have no structured risk assessment behind them — until legal, a regulator, or an incident forces the conversation. This course gives security architects, GRC professionals, and engineering managers a repeatable process to identify, score, and document AI risk against NIST AI RMF and EU AI Act requirements. Every deliverable is audit-ready and reusable on the next system you ship.
What You'll Learn
GenAI Risk Register
A scored, prioritized register for LLM apps, RAG pipelines, and agentic systems — mapping failure modes (hallucination, prompt injection, data leakage, model drift, tool call risk, supply chain exposure) to likelihood, impact, and ownership, including cascading risk chains traditional registers miss.
NIST AI RMF Assessment Report
Complete Map, Measure, and Manage assessment — risks scored across six impact categories with evidence, plus a risk treatment plan and remediation roadmap your engineering team can execute and your CISO can present. Audit-ready format.
EU AI Act + ISO 42001 Compliance Checklist
Risk tier classification with documented rationale — including edge cases at the high-risk boundary — plus deployer obligation mapping, ISO 42001 gap analysis, and a 90-day closure plan for legal sign-off.
Full Risk and Compliance Package
Risk register, NIST assessment, and compliance checklist in a single executive-readable package — with risk acceptance and escalation recommendations that hold up under CISO, legal, or auditor scrutiny.
Who Is This For?
This course is designed for:
Security Architects Adding AI to Their Risk Surface
Who are responsible for securing AI systems in production but lack a structured methodology to assess AI-specific risks beyond traditional threat modeling.
GRC Professionals Extending Frameworks to Cover AI
Who own enterprise risk and compliance programs and are being asked to extend existing controls to cover LLMs, RAG pipelines, and AI agents — without a clear starting point.
Engineering Managers Shipping AI Without Risk Documentation
Who are moving fast on AI features and know the risk layer is undocumented — before a compliance audit, a vendor review, or an incident makes it urgent.
Course Outline
4 weeks · 3 sessions per week
Projects You'll Ship
Leave with real work to show, not just a certificate.
GenAI Risk Register
A structured risk register for a real or provided AI system — LLM app, RAG pipeline, or agent — mapping GenAI-specific failure modes to calibrated likelihood, impact, cascading dependencies, and ownership. Scored and prioritized. Reusable as a living document and intake template for every AI system your organization ships.
NIST AI RMF Assessment Report
A complete Map, Measure, and Manage function assessment — risk categories scored across NIST's six impact dimensions, gaps documented with evidence, and a remediation roadmap your engineering team can execute and your CISO can present. Audit-ready format, directly handable to an external assessor.
Full AI Risk and Compliance Package
A unified risk documentation package integrating the risk register, NIST assessment, and EU AI Act + ISO 42001 compliance checklist — with an executive summary, risk acceptance and escalation recommendations, and a 90-day remediation roadmap. Structured for legal review, vendor audits, and regulatory response.
Your Instructors
Nahid Farady, PhD
Principal Tech Lead, AI Security & Privacy · Microsoft
⭐ 4.9 / 5
Nahid leads AI security, privacy, and responsible AI engineering at Microsoft Copilot, with prior roles at Google Cloud and Capital One CyberML. She holds a PhD from Virginia Tech and brings 10+ years of applied experience in cybersecurity, threat modeling, and ML deployment at scale. She also teaches AI and security as adjunct faculty at UC Berkeley.
What Students Say
⭐⭐⭐⭐⭐
"The risk register from Week 1 is now our standard intake form for every new AI feature. We catch failure modes before engineering starts, not after."
Alex Johnson
Security Architect · Lattice
⭐⭐⭐⭐⭐
"Running the NIST AI RMF assessment live in Week 2 surfaced three undocumented risks in our RAG pipeline that had been in production for six months. Worth the entire sprint."
Emma Lee
GRC Lead · Linear
⭐⭐⭐⭐⭐
"I brought our AI risk package to a vendor audit two weeks after the sprint ended. First time we had documentation that actually answered their questions."
Sam Patel
Engineering Manager · Cloudflare
Course Schedule
All sessions are instructor-led and live. Recordings available within 24 hours.
SUNDAY
9:00 AM PDT
Live ClassRisk taxonomy, NIST AI RMF, EU AI Act compliance — applied to real AI systems.
WEDNESDAY
6:00 PM PDT
Lab SessionHands-on assessment and documentation work on your own or provided systems.
THURSDAY
6:00 PM PDT
Build & ShipFinalize weekly deliverables with peer review and instructor scoring calibration.
Frequently Asked Questions
Related reading
The JD-backed research behind this course — from Dexity Intel.
AI Governance in 2026: How to Govern the AI You Ship →How far do you want to go?
Start free to experience our offering, choose the program length you would want to commit to.
You build. Nobody demos at you.
Every session is follow-along — you build the thing yourself while a practitioner works beside you. That is why the hours look long: they are yours to build in, with an expert on hand to guide you. None of it is a traditional lecture.
In the session, you'll: