Secure AI workloads and strengthen cloud identity protection using Microsoft Defender for Cloud and Microsoft Entra.

This course teaches how to secure AI services and Microsoft Foundry environments using cloud-native protections, implement identity and access controls with Microsoft Entra, and manage AI security posture using Microsoft Defender for Cloud.

  • Why get trained: Learn how to secure AI workloads using Microsoft Defender for Cloud, Microsoft Foundry, Microsoft Entra, Conditional Access and cloud-native security controls.
  • Why it matters: AI security capabilities help organizations reduce risk, strengthen identity governance and protect AI applications from emerging cloud threats.
  • Who should attend: Cloud security engineers, platform engineers, AI engineers and IT professionals responsible for securing AI workloads and cloud environments.

Build the capability to secure AI workloads, enforce identity controls and strengthen cloud security posture with Trainocate. HRD Corp Claimable.

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

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

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August 6, 2026 - August 6, 2026

Location: Kuala Lumpur
Modal: ILT
Availability: TBC
Exam:
Included
RM 1200

August 6, 2026 - August 6, 2026

Location: Online
Modal: VILT
Availability: TBC
Exam:
Included
RM 1200

November 12, 2026 - November 12, 2026

Location: Kuala Lumpur
Modal: ILT
Availability: TBC
Exam:
Included
RM 1200

November 12, 2026 - November 12, 2026

Location: Online
Modal: VILT
Availability: TBC
Exam:
Included
RM 1200
Trainocate exam and cert

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

Training & Certification Guide

Frequently Asked Questions

SC-5009 teaches you how to secure AI workloads and AI environments in Microsoft Azure.

This course focuses on protecting AI systems using Microsoft Defender for Cloud, Microsoft Entra, and Microsoft Foundry. Learners will understand how to secure AI identities, establish trust boundaries, and protect AI workloads from threats.

Key learning areas:

  • AI workload protection
  • AI identity and access security
  • Microsoft Defender for Cloud for AI
  • Security posture management for AI environments

Pro Tip: Focus on understanding AI-specific risks such as prompt injection and model exposure. These are increasingly important in enterprise AI environments.

It is designed for professionals responsible for securing AI and cloud environments.

The course targets individuals managing AI workloads and cloud-native security controls within Azure environments.

Best suited for:

  • Security engineers
  • Cloud security architects
  • AI platform engineers
  • Identity and access administrators

Pro Tip: If you already work in cybersecurity or cloud security, this course helps you specialize in one of the fastest-growing security domains.

You will learn how to secure AI systems using Microsoft security and identity tools.

The course emphasizes practical AI security skills required to protect cloud-hosted AI workloads and generative AI environments.

Skills gained:

  • Securing AI workloads with Defender for Cloud
  • Implementing identity controls using Microsoft Entra
  • Managing AI security posture
  • Protecting Microsoft Foundry environments

Pro Tip: AI security combines cloud security, identity, and governance. Building expertise across all three areas increases your long-term career value.

AI introduces new security risks that traditional cybersecurity tools were not designed to handle.

As organizations deploy generative AI and AI agents, they must secure models, prompts, APIs, identities, and data pipelines against emerging threats such as prompt injection and unauthorized access.

Key AI security challenges:

  • Prompt injection attacks
  • Model misuse and data leakage
  • Identity and access risks
  • AI workload exposure

Pro Tip: Understanding AI security early can position you ahead of many cybersecurity professionals as AI adoption accelerates.

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