Governing AI Workloads with AI Foundry

As organizations rapidly adopt artificial intelligence, ensuring that AI models and data pipelines remain secure, compliant, and cost-effective is a critical priority. This text-based course guides you through the foundational principles of governing modern AI workloads using AI Foundry. You will gain the skills to establish robust governance frameworks, manage resource quotas, control cloud costs, and secure access to AI assets. Through clear written explanations and practical scenario-based exercises, you will transition from understanding core compliance concepts to implementing real-world governance strategies. What you'll learn: - Understand the core principles of AI governance, risk management, and responsible AI practices - Configure policy-driven controls to ensure compliance with organizational and regulatory standards - Secure identity and access management for AI models, data sources, and computing resources - Manage the model lifecycle from deployment through monitoring and retirement - Monitor resource quotas, optimize cloud spending, and track key performance metrics - Apply zero-trust security concepts specifically tailored for AI-ready workloads The course begins with essential terminology and foundational governance concepts before guiding you through structured written walkthroughs for configuring access, policies, and cost-tracking tools. You will read real-world scenarios and complete practical review exercises designed to solidify your administrative skills. This course is designed for beginner cloud administrators, compliance officers, and IT professionals who are new to AI workload management, with no prior programming experience required. Start reading today to master the essentials of AI workload governance.