Secure AI solutions in the cloud by configuring AI workloads, applying cloud-native protections, and reinforcing security outcomes with identity controls. Learn how AI workloads authenticate, how trust boundaries are established, and how security posture and workload protection reduce risk using Microsoft Defender for Cloud and Microsoft Foundry. Extend these protections by using Microsoft Entra to design and apply identity and access controls that explain and harden earlier security decisions. Learning outcomes:

Apply security posture management and workload protection for AI services using Microsoft Defender for Cloud

Configure and secure Microsoft Foundry environments using cloud-native security controls

Design and apply identity and access controls for AI workloads using Microsoft Entra

Audience Profile

This course is intended for professionals responsible for securing and operating AI workloads in the cloud. The audience includes cloud security engineers, platform engineers, and application teams working with AI services who need to understand how workload protection, security posture, and identity controls apply to AI environments. Familiarity with Azure, cloud-native security concepts, and basic identity and access principles is recommended.

Course Syllabus

Protect Microsoft Foundry solutions by using Microsoft Defender for Cloud

• Understand how Microsoft Defender for Cloud supports AI security and governance in Azure
• Protect AI workloads with Microsoft Defender for Cloud
• Configure and manage guardrails in Microsoft Foundry
• Secure Microsoft Foundry environments