Securing Azure AI Workloads: Authentication, Authorization, and RBAC

As artificial intelligence becomes central to modern applications, securing access to AI models and data is a critical priority for developers and IT professionals. This course guides you through the foundational concepts of identity management specifically tailored for Azure AI environments. You will transition from understanding basic security principles to implementing robust authentication and authorization strategies. By learning how to configure role-based access control and managed identities, you will ensure your AI workloads remain secure, compliant, and resilient against unauthorized access. What you'll learn: - Learn the core principles of identity, authentication, and authorization within Azure cloud environments - Configure managed identities to securely connect applications to Azure OpenAI and AI Search without managing passwords - Apply Azure Role-Based Access Control (RBAC) to enforce the principle of least privilege across machine learning workspaces - Understand zero-trust security concepts and modern authentication flows for cloud-hosted AI models - Practice designing security policies that protect sensitive data used in AI training and deployment pipelines The course begins with essential definitions of identity management and authentication protocols, then progresses to step-by-step written explanations on configuring roles and securing Azure Machine Learning workspaces and OpenAI endpoints. Designed for IT professionals, cloud beginners, and developers looking to specialize in AI security, this program requires no prior cloud security experience. Start reading today to build a strong foundation in securing cloud-based artificial intelligence.