AI-200 Practice Test

AI-200 (Developing AI Cloud Solutions on Azure) is Microsoft's Associate-level exam for the Azure AI Cloud Developer Associate certification. It validates skills contributing to the back-end engineering of AI solutions on Azure — containerized hosting, AI data management services, event- and message-based integration, and securing, monitoring, and troubleshooting the resulting solutions.

The AI-200 exam follows Microsoft's standard Associate-level pricing and format: $165 USD, a 100-minute exam duration, and a passing score of 700 out of 1000. Pricing can vary slightly by country and is subject to change — confirm the exact current price on the official Microsoft Learn scheduling page before booking.

The passing score for AI-200 is 700 out of 1000, the same threshold used across nearly all Microsoft role-based certification exams. Microsoft uses scaled scoring, so 700 represents roughly 70% competency across all four exam domains rather than a simple raw percentage.

AI-200 covers four domains: Develop containerized solutions on Azure (20-25%) — Azure Container Registry, Container Registry Tasks, App Service container hosting, Container Apps, KEDA autoscaling, and AKS manifest deployments; Develop AI solutions by using Azure data management services (25-30%, the largest domain) — Cosmos DB for NoSQL vector search and change feed, Azure Database for PostgreSQL with pgvector and RAG patterns, and Azure Managed Redis caching and vector indexing; Connect to and consume Azure services (20-25%) — Service Bus, Event Grid, and Azure Functions; and Secure, monitor, troubleshoot Azure solutions (20-25%) — Key Vault, App Configuration, OpenTelemetry, and KQL.

AI-200 is a scenario-heavy Associate exam that assumes hands-on backend engineering experience — you are given a realistic architecture problem and asked to pick the correct Azure service or configuration, not recall a definition. The vector-database domain (Cosmos DB, pgvector, Azure Managed Redis) is the newest and least familiar material for most candidates, even those experienced with traditional Azure app development, since retrieval-augmented generation patterns are a recent addition to Azure's data platform.

Candidates already comfortable with Azure Container Apps, AKS, and Python or another Azure SDK language should plan 4-6 weeks, focused mostly on the vector-database domain (Cosmos DB, pgvector, Azure Managed Redis) since it carries the highest exam weight. Candidates newer to Azure application development should plan 10-12 weeks total. We recommend studying the Microsoft Learn path first, then working through 500 scenario-based practice questions with emphasis on the data-management and containerization domains.

There are no enforced prerequisites to register for AI-200, but Microsoft designed the exam for candidates proficient in Azure SDKs and third-party SDKs, Azure data management services, Azure monitoring and troubleshooting, Azure messaging and eventing, vector databases, Python programming, and containerized application deployment on Azure. Hands-on backend development experience is strongly recommended over pure conceptual study.

AI-200 is aimed at developers and backend engineers who build and operate the infrastructure behind AI solutions on Azure — connecting containerized services to vector databases, message queues, and event-driven pipelines — rather than data scientists building the models themselves. It complements AI-102/AI-103-style exams, which focus more on consuming Azure AI services (vision, language, generative AI) directly, by testing the surrounding backend platform engineering.