Governing AI Services with Azure Policy

As organizations rapidly adopt artificial intelligence, maintaining security, compliance, and cost control across AI workloads is more critical than ever. Managing these services manually leads to configuration drift and potential security risks. This course teaches you how to automate the governance of AI services using Azure Policy. You will learn how to establish guardrails that enforce responsible AI practices, restrict unauthorized model deployments, and ensure regulatory compliance without slowing down development. What you'll learn: - Understand the core concepts of cloud governance, policy-as-code, and responsible AI principles. - Configure built-in Azure Policy definitions specifically designed for cognitive services and generative AI workloads. - Create custom policy definitions to enforce resource limits, private endpoints, and data residency requirements. - Apply compliance auditing to identify non-compliant AI deployments across your cloud environment. - Remediate existing non-compliant AI services automatically using policy remediation tasks. - Practice writing and testing policy rules through structured written exercises and real-world scenarios. You will start by exploring foundational governance terms and the structure of policy definitions before moving into practical scenarios for securing AI endpoints and monitoring compliance. This course is designed for beginners, cloud administrators, and security professionals who want to govern AI deployments, with no prior policy-writing experience required. Start reading today to bring order, security, and consistent compliance to your organization's AI initiatives.