Govern AI-ready infrastructure
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This course teaches how to govern AI-ready infrastructure with Microsoft Foundry by enforcing policies, secure access, managing costs, regulating model behavior, and monitor compliance through practical, real-world governance scenarios.
Prerequisites
- Familiarity with Azure fundamentals, including subscriptions, resource groups, and basic resource management concepts.
- A foundational understanding of AI and machine learning workloads, such as Azure OpenAI and model deployments.
- Experience using the Azure portal or Azure CLI to deploy and configure resources.
- Basic knowledge of identity, access, and security concepts in Azure, such as RBAC and Microsoft Entra ID.
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Modules in this learning path
Learn how to govern AI workloads using Microsoft Foundry by enforcing policies, managing costs, ensuring compliance, and applying responsible AI guardrails through hands‑on governance scenarios and exercises.
Learn to govern AI workloads using Microsoft Foundry by enforcing policy‑driven controls, securing identity access, monitoring compliance, and managing model lifecycle, quotas, and costs through practical, hands‑on exercises.
Implement enterprise AI governance with Microsoft Foundry by understanding the governance framework, configuring policy‑driven controls, enforcing quotas and safeguards, and applying hands‑on exercises to balance compliance, security, cost management, and innovation.
Discover classify AI assets enforce Azure Policy guardrails track data lineage and implement hands‑on governance controls securing compliant auditable AI deployments across infrastructure pipelines and sensitive data workflows.
Design and deploy governed AI infrastructure by understanding governance frameworks, enforcing policies and access controls, implementing responsible AI safeguards, and completing hands-on exercises to ensure compliant, secure AI workloads.