Apply governance controls to AI-ready workloads
Intermediate
Administrator
AI Engineer
Azure
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.
Learning objectives
By the end of this module, you're able to:
- Configure Microsoft Purview to discover and classify AI infrastructure assets
- Implement Azure Policy guardrails for AI resource provisioning and management
- Establish data lineage tracking for AI training datasets and model outputs
- Monitor AI workload compliance using Microsoft Purview audit logs and reports
- Design access controls that protect AI models and sensitive training data
Prerequisites
- Familiarity with Azure fundamentals, including subscriptions, resource groups, and Azure role-based access control (RBAC)
- Basic understanding of Azure AI services and AI workload concepts, such as models, pipelines, and deployments
- Awareness of governance, security, and compliance principles, including data residency and policy enforcement
- Experience navigating the Azure portal to review resources, policies, and monitoring information
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