Securing Azure Infrastructure for AI Workloads

Deploying AI models and data pipelines requires a robust security foundation to protect sensitive organizational assets. This course guides you through configuring essential security controls to safeguard your cloud-based AI-ready environments. You will transition from understanding basic cloud security concepts to confidently implementing identity management, role-based access control, and secure service communication for AI workloads. What you'll learn: - Understand foundational cloud security terminology and Azure security baselines - Configure Entra ID security principals to manage user and application access - Implement managed identities for secure service-to-service communication without hardcoded secrets - Apply modern Zero Trust principles to AI workspaces and storage resources - Configure role-based access control tailored specifically for data science teams The course begins with core security definitions and identity concepts before moving into step-by-step written explanations on configuring access policies, network isolation, and identity federation. You will learn through clear, text-based scenarios and structured security configuration examples. Designed for IT beginners, aspiring cloud administrators, and security novices, this course requires no prior experience with cloud security. Start building a secure foundation for your organization's AI initiatives today.