This unit introduces enterprise Generative AI use cases, the shared responsibility model, and the regulatory and control frameworks that govern Azure OpenAI deployments. Students will learn how to select and evaluate security controls, compare hosting models, and begin using the Microsoft Cloud Security Benchmark and Azure Policy to secure Azure OpenAI at scale, building a foundation for hands-on implementation in later units.
Learning Objectives
- analyze common enterprise Generative AI use cases to identify associated security, privacy, and compliance risks specific to Azure OpenAI deployments
- evaluate shared responsibility models and relevant regulatory/control frameworks to determine required governance and controls for cloud-hosted AI services
- compare OpenAI hosting models and recommend appropriate hosting and control strategies based on risk, data residency, and compliance requirements
- apply the Microsoft Cloud Security Benchmark and author basic Azure Policy definitions to demonstrate enforcement of security controls for Azure OpenAI resources at scale
Curriculum
- 1 Section
- 9 Lessons
- 30 hours
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- Unit 1 — Governance and Security for Azure OpenAI9
- 1.1Common Use Cases for Generative AI in the Enterprise20 mins
- 1.2Shared AI Responsibility Model20 mins
- 1.3Regulation and Control Frameworks20 mins
- 1.4Key Takeaways20 mins
- 1.5References20 mins
- 1.6On the Importance of Selecting Appropriate Security Controls20 mins
- 1.7Comparing OpenAI Hosting Models20 mins
- 1.8Evaluating Security Controls with MCSB20 mins
- 1.9Using Azure Policy to Secure Azure OpenAI at Scale20 mins
Instructor
Free
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