Microsoft's skills measured for AI-200 as of unknown, mapped to the chapters of Ultra Transcenders AI-200: Developing AI Cloud Solutions on Azure.
| Objective | Chapters |
|---|---|
| Develop containerized solutions on Azure (20–25%) | |
| Implement container application hosting | 1. Azure Container Registry and ACR Tasks; 2. Containers on Azure App Service |
| Implement container-orchestrated solutions | 3. Azure Container Apps: environments, revisions and secrets; 4. Scaling Container Apps with KEDA; 5. Deploying to Azure Kubernetes Service with manifests; 6. Monitoring and troubleshooting AKS and Container Apps |
| Develop AI solutions by using Azure data management services (25–30%) | |
| Develop AI solutions by using Azure Cosmos DB for NoSQL | 7. Azure Cosmos DB for NoSQL for AI apps; 11. Azure Functions: serverless APIs, triggers and bindings |
| Develop AI solutions by using Azure Database for PostgreSQL | 8. Azure Database for PostgreSQL for vector workloads |
| Integrate Azure Managed Redis in AI solutions | 9. Azure Managed Redis for caching and vector search |
| Connect to and consume Azure services (20–25%) | |
| Develop event- and message-based AI solutions | 10. Messaging and events: Service Bus and Event Grid |
| Develop and implement Azure Functions | 11. Azure Functions: serverless APIs, triggers and bindings |
| Secure, monitor, and troubleshoot Azure solutions (20–25%) | |
| Implement secure Azure solutions | 12. Security and observability: Key Vault, App Configuration, OpenTelemetry and KQL |
| Monitor and troubleshoot Azure solutions | 6. Monitoring and troubleshooting AKS and Container Apps; 12. Security and observability: Key Vault, App Configuration, OpenTelemetry and KQL |
The full list of tasks under each objective is in the official AI-200 study guide and practice assessment. The book is organised by technology, so one chapter often serves several objectives.