Added introduction unit

This module covers configuring secure infrastructure for AI agents, including RBAC role assignments, managed identities, and Cosmos DB deployment.

Author: Susmitha221

learn-pr/wwl-azure/manage-secure-ai-ready-infrastructure/includes/1-introduction.md

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+## Learning objectives
+
+- Configure Azure RBAC role assignments to enforce least-privilege access for AI infrastructure components
+- Implement system-assigned managed identities to enable keyless authentication between Azure services
+- Deploy and configure Azure Cosmos DB for NoSQL as a conversation and metadata store for AI agents
+- Evaluate security and governance considerations for production AI workloads on Azure
+
+
+In this module, you configure the secure infrastructure that Contoso's AI agents require. You assign RBAC roles to grant specific permissions without over-provisioning access, enable managed identities to eliminate connection string management, and deploy Cosmos DB as a scalable conversation store with optimized partition keys and time-to-live policies. By the end of this module, you have hands-on experience building production-ready AI infrastructure that satisfies security auditors and supports global-scale deployments.
+
+## More resources
+
+- [What is Azure Role-Based Access Control (Azure RBAC)?](/azure/role-based-access-control/overview) - Comprehensive overview of RBAC concepts, scope hierarchy, and built-in roles
+- [What are managed identities for Azure resources?](/entra/identity/managed-identities-azure-resources/overview) - Introduction to system-assigned and user-assigned managed identities with use case examples
+- [Welcome to Azure Cosmos DB](/azure/cosmos-db/introduction) - Overview of Cosmos DB capabilities, consistency levels, and global distribution features