Secure AI workloads in Azure using cloud native protection and identity controls.
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.
Module 1: Protect Microsoft Foundry solutions by using Microsoft Defender for Cloud
Module 2:Secure AI identity infrastructure with Microsoft Entra
After this course participants should be able to:
Learners should have:
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.
