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SC-5009 Secure AI solutions in the cloud using Microsoft Defender for Cloud and Microsoft
AI in the cloud unlocks enormous potential – but only with the right protection. Clear security architectures prevent models, data, and interfaces from becoming attack surfaces.
Key topics
- Designing and implementing security architectures for cloud AI.
- Using Defender technologies to detect and respond to attacks.
- Securing models, data pipelines, and APIs in a structured way.
- Identifying and meeting compliance requirements in AI projects.
- Setting up automated security analysis and continuous monitoring.
Prerequisite
Basic knowledge of cloud services and an understanding of IT security concepts will make it easier to get started.
Target group
Suitable for cloud engineers, security professionals, IT administrators, and technical leaders who want to operate AI solutions securely in the cloud.
Structured security for cloud AI reduces risks and creates the foundation for high-performing, trustworthy digital systems.
Course Content
AI Security and Governance in Azure with Microsoft Defender for Cloud
- Getting to know the core AI services in Azure.
- Assessing security risks for AI workloads in Azure.
- Setting up AI guardrails and safeguards in Azure.
- Using Azure security and governance tools to support AI workloads.
Securing AI workloads with Microsoft Defender for Cloud
- Activating the AI Workload Plan in Defender for Cloud.
- Evaluating the Data and AI Security Dashboard.
- Assessing and improving AI security posture with CSPM (Cloud Security Posture Management).
- Detecting AI threats at runtime with Cloud Workload Protection (CWP).
- Investigating AI security alerts using prompt evidence in Microsoft Defender XDR.
Configure and manage guardrails in Microsoft Foundry
- Getting to know guardrails and Microsoft Content Safety.
- Understanding security controls in Microsoft Foundry.
- Testing and trying out integrated guardrails.
- Creating and managing blocklists in Microsoft Foundry.
- Configuring and deploying guardrails in production.
- Selecting and fine-tuning optimal guardrails for your AI workloads.
Securing Microsoft Foundry environments
- Setting up access control for Microsoft Foundry with Microsoft Entra ID.
- Managing permissions within Microsoft Foundry projects.
- Securing Foundry secrets with Azure Key Vault (preview).
- Isolating networks with Managed Virtual Network and Private Link.
- Setting up and enabling diagnostic logging in Microsoft Foundry.
Up to 100% funding for your continuing education
Attractive funding opportunities are available for numerous continuing education programs – depending on the funding program, up to 100% funding is possible.
The requirement is that you live or work in Germany. Our funding opportunities are not available outside of Germany.
Funding opportunities are available for career starters, job seekers, career changers, startups, experienced professionals, those seeking career advancement, and specialists.
Why do cloud AI solutions need special protection?
- AI processes highly sensitive data and drives automated decisions. Without proper safeguards, real business risks arise and compliance requirements can be violated.
What threats do unsecured AI workloads create?
- Data breaches, tampered models, and unauthorized access threaten the integrity, availability, and trust in AI-based systems.
What does Microsoft Defender for Cloud do for AI workloads?
- Defender for Cloud provides centralized monitoring, threat detection, and security assessments for AI workloads across hybrid and multi-cloud environments.
How can AI models be actively defended against attacks?
- Protect training data, restrict access rights, set up monitoring, and detect anomalies in model behavior at an early stage.
Why is compliance so important for cloud-based AI?
- Regulatory requirements demand transparent, traceable, and secure processing of sensitive data in AI systems.
What advantages do integrated security tools bring to the security strategy?
- Automated analyses and consistent security policies close gaps faster and speed up response to threats.
In which industries is secure AI deployment especially critical?
- Healthcare, financial services, and critical infrastructure set the highest security standards for AI-based processes.
What are the benefits of specializing in AI security?
- Better-protected systems, growing market demand, and a stronger position in cloud and security projects.
