AI-200 Azure AI Cloud Developer Study Notes

Prepare for Microsoft AI-200: Developing AI Cloud Solutions on Azure — the Azure AI Cloud Developer Associate certification. Free study notes with code samples, practice questions, and mock exams.

For developers building back-end AI solutions with Python, containers, vector databases, and Azure services.

Prepared by Surafel Melaku · sura.work · GitHub

Study materials Practice questions Practice exams

Official AI-200 study guide →

Important skills to focus on

Four core skill areas for the AI-200 exam — all covered in the study materials below.

AI Solution Development & Integration

Build and integrate AI solutions on Azure by leveraging containerized compute, event-driven AI pipelines, and serverless functions for scalable AI deployments.

4 learning paths

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Vector Database Management

Configure and manage vector-enabled databases on Azure for efficient storage, retrieval, and processing of large-scale AI models and datasets.

3 learning paths

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Distributed Observability & Monitoring

Implement distributed observability for AI solutions, ensuring comprehensive monitoring and performance tracking across cloud-based applications and models.

1 learning path

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AI Security & Secret Management

Manage sensitive data and secrets for AI applications by utilizing Azure's secret management tools, ensuring secure access to AI models and resources across the development lifecycle.

1 learning path

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Exam domains

Containerized Solutions

20–25% of exam

Azure Container Registry, Container Apps, AKS, and KEDA for AI workloads.

Data Management for AI

25–30% of exam

Cosmos DB, PostgreSQL with pgvector, and Azure Managed Redis for RAG and vector search.

Azure Services Integration

20–25% of exam

Service Bus, Event Grid, and Azure Functions for event-driven AI solutions.

Secure, Monitor & Troubleshoot

20–25% of exam

Key Vault, App Configuration, OpenTelemetry, and KQL for observability.

Azure SDK and Azure CLI

Quiz of exam

Azure CLI commands and Python SDK classes/methods for deploying, configuring, and troubleshooting AI solutions.