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| 1 | +### YamlMime:Module |
| 2 | +uid: learn.wwl.apply-governance-controls-ai-ready-workloads |
| 3 | +metadata: |
| 4 | + title: "Apply governance controls to AI ready workloads" |
| 5 | + description: "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." |
| 6 | + ms.date: 02/02/2026 |
| 7 | + author: wwlpublish |
| 8 | + ms.author: bradj |
| 9 | + ms.topic: module |
| 10 | + ms.service: azure |
| 11 | +title: "Apply governance controls to AI ready workloads" |
| 12 | +summary: 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. |
| 13 | +abstract: | |
| 14 | + By the end of this module, you're able to: |
| 15 | + - Configure Microsoft Purview to discover and classify AI infrastructure assets |
| 16 | + - Implement Azure Policy guardrails for AI resource provisioning and management |
| 17 | + - Establish data lineage tracking for AI training datasets and model outputs |
| 18 | + - Monitor AI workload compliance using Microsoft Purview audit logs and reports |
| 19 | + - Design access controls that protect AI models and sensitive training data |
| 20 | +prerequisites: | |
| 21 | + - Familiarity with Azure fundamentals, including subscriptions, resource groups, and Azure role-based access control (RBAC) |
| 22 | + - Basic understanding of Azure AI services and AI workload concepts, such as models, pipelines, and deployments |
| 23 | + - Awareness of governance, security, and compliance principles, including data residency and policy enforcement |
| 24 | + - Experience navigating the Azure portal to review resources, policies, and monitoring information |
| 25 | +iconUrl: /training/achievements/generic-badge.svg |
| 26 | +levels: |
| 27 | +- intermediate |
| 28 | +roles: |
| 29 | +- administrator |
| 30 | +- ai-engineer |
| 31 | +products: |
| 32 | +- azure |
| 33 | +subjects: |
| 34 | +- infrastructure |
| 35 | +units: |
| 36 | +- learn.wwl.apply-governance-controls-ai-ready-workloads.introduction |
| 37 | +- learn.wwl.apply-governance-controls-ai-ready-workloads.discover-classify-ai-infrastructure-assets |
| 38 | +- learn.wwl.apply-governance-controls-ai-ready-workloads.implement-azure-policy-guardrails-workloads |
| 39 | +- learn.wwl.apply-governance-controls-ai-ready-workloads.establish-data-lineage-track-pipelines |
| 40 | +- learn.wwl.apply-governance-controls-ai-ready-workloads.exercise-configure-governance-ai-deployment |
| 41 | +- learn.wwl.apply-governance-controls-ai-ready-workloads.knowledge-check |
| 42 | +- learn.wwl.apply-governance-controls-ai-ready-workloads.summary |
| 43 | +badge: |
| 44 | + uid: learn.wwl.apply-governance-controls-ai-ready-workloads.badge |
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