AI & Agent Governance and Safety
Not Started0 / 10 complete
Open a video or resource link, watch it, then check its box to track your progress and unlock what comes next.
10 lessons3 levels1 capstone project
Govern AI and autonomous agents across the full lifecycle: risk classification, accountable ownership, policy and control design, model/agent inventories, permissions, human oversight, safety testing, content safeguards, auditability, incident response, regulatory alignment and continuous monitoring. Apply NIST, OWASP and enterprise Responsible AI practices to production agentic systems.
BASIC
- The Importance of AI Governance — IBM Technology (8 min selected)
A fast enterprise mental model for governance, transparency, explainability and responsible AI workflows. - What Is AI Governance? — IBM Research (4 min)
Connect governance to AI safety, risk levels and the difficulty of providing safety guarantees for generative AI. - Introduction to the AI Risk Management Framework (AI RMF 1.0) — NIST (10 min selected)
Learn the core risk-management structure used to organize trustworthy AI outcomes across the lifecycle.
INTERMEDIATE
- AI Risk Management Framework Playbook — NIST
Translate governance principles into recommended actions, evidence and operating practices. - Responsible AI Series — Microsoft Learn
Operationalize fairness, reliability and safety, privacy/security, inclusiveness, transparency and accountability. - Content Safety — Microsoft AI Show
See practical mitigation layers, harmful-content detection, severity thresholds and Content Safety Studio in action.
ADVANCED
- AI Governance Explained: How to Manage AI Agents in Your Organization — InfosecTrain
Apply governance specifically to enterprise agents: policy, access, data controls, monitoring, scaling and accountability. - Agentic Security Open Workshop: Agentic AI Threats and Mitigations — OWASP
Threat-model memory, tools, identity and multi-agent propagation; connect safety governance to concrete attack paths. - Securing Generative AI: A Baseline in the Security Landscape — AWS re:Inforce
Extend governance into production security controls, cloud risk and defense-in-depth for generative AI systems.