AI Workload Governance and Compliance with Azure Policy

As organizations rapidly adopt artificial intelligence, ensuring that AI systems are secure, compliant, and auditable is more critical than ever. This course helps you navigate the complexities of AI risk management by establishing robust guardrails from the ground up. You will transition from understanding basic compliance theory to actively implementing structured governance frameworks. Through clear, step-by-step written explanations and practical configuration scenarios, you will learn how to secure sensitive data workflows and maintain full visibility over your AI infrastructure pipelines. What you'll learn: Understand foundational AI governance principles, risk frameworks, and key compliance terminology; Classify AI assets and sensitive data to ensure proper handling and storage; Enforce cloud guardrails using Azure Policy to prevent unauthorized resource deployment; Track data lineage to maintain auditability and transparency throughout the AI lifecycle; Implement zero-trust security concepts within your AI infrastructure; Configure automated compliance checks and audit logs for continuous monitoring. The curriculum begins with essential terminology and foundational definitions of AI risk before moving into practical policy enforcement, lineage tracking, and compliance workflows. You will read detailed breakdowns and analyze policy configurations to solidify your learning. This course is designed for beginners, cloud administrators, and compliance professionals new to AI governance, with no advanced prerequisites required. Start building safer, more transparent AI systems today by mastering these essential governance controls.