Overview
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
Why Choose KORNERSTONE
- Accredited, practitioner-led, expert certificate trainers to provide high quality training
- Official training material included
- Practical, scenario-based learning – focus on application, not just theory
- Excellent Passing Rate
Skills Covered
- Understand AI workload risks and how Microsoft Defender for Cloud identifies and protects AI assets
- Enable the AI Workloads plan and use Cloud Security Posture Management (CSPM) to discover and remediate misconfigurations
- Use Cloud Workload Protection (CWP) to detect runtime threats targeting AI components
- Investigate AI security alerts in Microsoft Defender XDR
- Configure and manage guardrails in Microsoft Foundry to prevent unsafe or policy-violating model behavior
- Learn how to secure identities used by AI workloads in Azure.
- Understand workload identity architecture, configure access to Azure resources, apply Conditional Access policies, and investigate identity risk by using Microsoft Entra.
Prerequisites
Familiarity with Azure, cloud-native security concepts, and basic identity and access principles is recommended.
Target Audience
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.
Course Curriculum
Module 1: 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
Module 2: Secure AI identity infrastructure with Microsoft Entra
- Understand identity architecture for AI workloads
- Implement access management for Azure resources
- Plan, implement, and administer Conditional Access
- Manage Microsoft Entra Identity Protection
Dates & Locations
Exam & Certification
Microsoft Applied Skills: Secure AI Solutions in the Cloud
Validate your technical skills and open doors to new possibilities of advancement with Microsoft Applied Skills.
To earn this Microsoft Applied Skills credential, learners demonstrate the ability to secure AI solutions in the cloud. Candidates for this credential should have a solid understanding of working with Microsoft Defender for Cloud, and Microsoft Foundry.
They should also have experience with the Azure portal, and be familiar with security and AI concepts in Azure.
Evaluated in this assessment
- Configure security for AI services in Microsoft Defender for Cloud
- Configure model guardrails and controls in Microsoft Foundry
- Configure security settings for an Azure Microsoft Foundry environment
