Overview What You Will Learn Curriculum Instructor

Course Overview

Azure OpenAI enables organizations to deploy powerful generative AI capabilities in enterprise environments, but it also introduces new security, privacy, and governance challenges. This course focuses on securing Azure OpenAI workloads by applying Microsoft cloud security controls, identity management, and compliance practices. It helps learners understand how to protect AI services, data, and access layers while aligning with modern cloud security and zero-trust principles.

This course begins with an introduction to Azure OpenAI services, the shared responsibility model, and key security concepts like RBAC, MFA, and API key management. It then covers implementing security best practices using Microsoft Entra ID, Defender for Cloud, network segmentation, private endpoints, NSGs, content filtering, and DLP strategies. You will design secure AI architectures with integrated identity, data, and network security layers, enforce governance using Azure Policy, and manage the full AI lifecycle, including versioning, drift detection, and secure decommissioning. The course also addresses compliance with industry standards, real-time monitoring using Azure Sentinel, threat detection and investigation, secure secret management with Azure Key Vault, and automation through Azure Monitor, Logic Apps, and Sentinel playbooks.

You will learn to securely deploy, monitor, govern, and maintain Azure OpenAI workloads while minimizing risks and ensuring compliance in enterprise cloud environments.

What You Will Learn

  • Implement secure access and identity controls for Azure OpenAI using RBAC and MFA.
  • Design and deploy secure AI architectures with network and data protection.
  • Apply security monitoring and threat detection using Azure Sentinel and Defender for Cloud.
  • Enforce governance and compliance using Azure Policy and security automation.
  • Manage AI workload lifecycle securely, including drift detection and secure decommissioning.

Program Curriculum

  • Overview of Azure OpenAI Services and Emerging Security Risks
  • Exploring Azure Security Fundamentals for AI
  • Introduction to RBAC, MFA, and API Key Management in AI Context
  • Understanding the Shared Responsibility Model in Azure OpenAI Deployments
  • Chapter 1 Quiz

  • Implementing RBAC Using Microsoft Entra ID for AI Services
  • Configuring MFA for Admin and Service Accounts
  • Secure API Endpoints, Manage API Keys, and Implement Least Privilege Access
  • Using Microsoft Defender for Cloud: Implementation Workflows for AI Workloads
  • Implementing Network Security Best Practices
  • Network Segmentation and Private Endpoints
  • Network Security Groups (NSGs) for AI Resource Isolation
  • Content Filtering and Data Loss Prevention (DLP) Strategies
  • Chapter 2 Quiz

  • Designing Secure AI Solution Architectures in Azure
  • Identity, Data, and Network Security Layers
  • Integration of Compliance and Threat Detection Tools
  • Using Azure Policy to Enforce Governance and Security Standards
  • Conducting Security Audits and Compliance Reviews During Deployment
  • Lifecycle Management Practices
  • Versioning, Drift Detection, and Change Auditing
  • Secure Decommissioning of AI Resources
  • Chapter 3 Quiz

  • Ensuring Compliance with Microsoft and Industry Standards
  • Monitoring AI Workloads Using Azure Sentinel
  • Real-time Threat Detection and Investigation
  • Correlating Logs and Signals Across Services
  • Using Azure Key Vault to Manage Secrets, Tokens, and Certificates
  • Setting Up Automation and Security Alerts for AI Workloads
  • Azure Monitor, Azure Logic Apps, and Sentinel Playbooks
  • Response Automation Workflows for Threats and Misconfigurations
  • Continuous Improvement Through Audit Trails and Feedback Loops
  • Chapter 4 Quiz
Load more modules

Instructor

Juraj Šimunec

Juraj Šimunec is Microsoft 365 Engineer experienced with setup and administration of complete M365 platform. His main area of focus is to provide best possible experience for users, but at the same time following best security practices in tenant configuration and integration with various workloads.

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