AI is transforming enterprise operations—and so are the risks that come with it. This program prepares security managers, compliance leads, and governance professionals to build and operate responsible AI systems in Microsoft-powered environments. You’ll apply frameworks like ISO/IEC 42001, NIST AI RMF, Microsoft’s Responsible AI Standard v2, GDPR, SOC 2, and FAIR to real-world scenarios across the full AI governance lifecycle.

Across five focused courses, you’ll design governance structures, evaluate ethical AI use cases, manage AI-specific risks, protect privacy, and secure model deployments in Azure Machine Learning. Each course connects technical controls with leadership responsibilities—so you can drive policy, coordinate across teams, and communicate risk and compliance status to executive stakeholders.

This program is designed for experienced cybersecurity and IT professionals moving into AI governance, compliance, or security strategy roles. Ideal for those with three to seven years of experience in security, risk, or data governance who are responsible for or preparing to lead AI oversight functions within their organizations.

Applied Learning Project

Each long course in this program includes a hands-on project that integrates the skills you’ve built across that course. Projects are scenario-based and mirror real governance and security workflows —from drafting a RACI matrix and policy gap analysis to building a risk register with FAIR exposure estimates and a STRIDE threat model. The LC 4 project synthesizes five short courses — GDPR compliance, DPIA analysis, transformer security, Azure ML defence-in-depth, and CVE response decisions — into a single audit-ready Privacy & Secure Operations Compliance Package for a regulated AI deployment. You’ll produce practical deliverables like policy documents, compliance audit summaries, risk treatment memos, and privacy compliance packages that reflect the kind of work AI governance and cybersecurity professionals do in real organizations.