Securing Developer AI Environments with Purview

As organizations rapidly adopt generative AI, securing developer environments and preventing sensitive data leaks has become a critical priority. This course guides you through using Purview to gain visibility and establish guardrails around AI development. You will learn how to identify shadow AI, assess data exposure risks, and implement robust security policies. By understanding how to apply dynamic enforcement based on user risk and data sensitivity, you will be able to foster safe AI innovation within your team. What you'll learn: - Understand the foundational concepts of AI security and zero-trust data protection. - Discover unauthorized generative AI applications and assess organizational risk. - Configure data classification and sensitivity labels for developer environments. - Implement dynamic access controls based on real-time user behavior analysis. - Apply data loss prevention policies specifically tailored for AI interactions. The course begins with core terminology and foundational security principles before moving into detailed written guides for configuring discovery, monitoring, and policy enforcement. You will read real-world scenarios and practice analyzing risk metrics through structured written exercises. This beginner-friendly course is designed for security administrators, developers, and compliance professionals looking to secure AI workflows, with no prior Purview experience required. Start reading today to build a secure foundation for AI development in your organization.