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218+ Free AI-200 Practice Questions

Prepare for the Microsoft Certified: Azure AI Cloud Developer Associate (AI-200) exam with instant access — no signup required.

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2026 Statistics

Key Facts: AI-200 Exam

700/1000

Passing Score

Microsoft (typical for role-based associate)

Not published

Question Count

Microsoft Learn AI-200 certification page

120 min

Exam Duration

Microsoft Learn AI-200 certification page

Regional

Exam Price

Microsoft Learn AI-200 certification page

4 domains

Official Skills Areas

Microsoft Learn AI-200 study guide

Annual

Free Renewal

Microsoft Learn

AI-200 is Microsoft's associate certification exam for backend and AI cloud developers. Microsoft provides 120 minutes and requires a scaled score of 700 or greater, but does not publish an exact question count. The official four-domain outline covers containerized Azure solutions (20-25%), AI solutions using Azure data services (25-30%), connecting to and consuming Azure services (20-25%), and security, monitoring, and troubleshooting (20-25%).

Sample AI-200 Practice Questions

Try these sample questions to test your AI-200 exam readiness. Each question includes a detailed explanation. Start the interactive quiz above for the full 218+ question experience with AI tutoring.

1Which Azure compute service is the most appropriate choice for hosting a containerized AI inference microservice that needs autoscaling, scale-to-zero, and managed networking, without managing Kubernetes directly?
A.Azure Container Apps
B.Azure Service Fabric
C.Azure Spring Apps
D.Azure Batch
Explanation: Azure Container Apps is a managed serverless container platform built on Kubernetes/KEDA that supports HTTP/event-driven autoscaling, scale-to-zero, revisions, traffic splitting, managed identities, and Dapr — all without exposing the Kubernetes API. It is the recommended starting point for containerized AI microservices.
2An AI Cloud Developer needs to deploy an AI inference container that requires fine-grained control over node pools, GPUs, and Kubernetes resources. Which Azure service should they choose?
A.Azure Functions Consumption plan
B.Azure Kubernetes Service (AKS)
C.Azure App Service Web Apps
D.Azure Logic Apps
Explanation: Azure Kubernetes Service (AKS) gives you full Kubernetes control, including custom node pools, GPU SKUs, and advanced networking. It is appropriate when Container Apps' abstractions are insufficient. It comes with higher operational responsibility than Container Apps.
3Which Azure Functions hosting plan is best for a low-latency AI API endpoint that must avoid cold-start delays?
A.Consumption plan
B.Premium plan or Flex Consumption with always-ready instances
C.Free tier
D.App Service Free F1
Explanation: Premium and Flex Consumption plans for Azure Functions support pre-warmed (always-ready) instances, eliminating cold starts and providing VNet integration. The basic Consumption plan has cold-start latency that can be problematic for user-facing AI APIs.
4An AI cloud app must call Azure OpenAI from Azure Container Apps without storing API keys. Which authentication mechanism should you configure?
A.API key in plain environment variable
B.User-assigned managed identity with Cognitive Services OpenAI User role on the Azure OpenAI resource
C.Personal access token of a developer
D.Anonymous access
Explanation: Azure Container Apps support both system- and user-assigned managed identities. Assigning a user-assigned identity and granting it the Cognitive Services OpenAI User RBAC role on the Azure OpenAI resource enables keyless, RBAC-based authentication without secret management.
5Which Azure data service supports vector embeddings via the pgvector extension and is recommended in the AI-200 curriculum for vector-enabled AI workloads on PostgreSQL?
A.Azure SQL Managed Instance
B.Azure Database for PostgreSQL with pgvector extension
C.Azure Files Premium
D.Azure Table Storage
Explanation: The AI-200 curriculum highlights Azure Database for PostgreSQL with the pgvector extension for storing and querying vector embeddings alongside relational data. pgvector adds a vector type and ANN indexes (HNSW, IVFFlat) suitable for RAG and similarity search.
6Which Azure Cosmos DB API is most appropriate for storing JSON documents with embedded vector embeddings used by an AI app?
A.Azure Cosmos DB for NoSQL with vector search support
B.Cosmos DB for Cassandra
C.Cosmos DB for Gremlin
D.Cosmos DB for Table
Explanation: Azure Cosmos DB for NoSQL supports vector search natively, allowing you to store embeddings alongside JSON documents and query them with vector indexes. It is the AI-200 curriculum's reference NoSQL choice for vector-enabled data patterns.
7Which Azure cache service is positioned in the AI-200 curriculum for caching, streaming, and vector search at low latency?
A.Azure Cache for Memcached
B.Azure Managed Redis (with vector search support)
C.Azure CDN
D.Azure Files
Explanation: Azure Managed Redis (the next-generation managed Redis offering) supports caching, streams, and vector search with Redis's vector index types. The AI-200 curriculum calls it out as the preferred Redis option for AI app caching, streaming, and vector workloads.
8Which Azure messaging service is best for decoupling a long-running AI processing pipeline from a public REST API by buffering work as messages?
A.Azure Service Bus queue
B.Azure DNS
C.Azure ExpressRoute
D.Azure Front Door
Explanation: Azure Service Bus queues provide durable, ordered, transactional messaging suitable for decoupling synchronous APIs from long-running AI processing. Workers consume messages and scale based on queue depth. Service Bus also offers topics for publish/subscribe patterns.
9Which Azure service is best suited as the eventing backbone that triggers an AI processing function when a new file lands in Blob Storage?
A.Azure Event Grid (with Blob Storage events)
B.Azure Notification Hubs
C.Azure Front Door
D.Azure Bastion
Explanation: Azure Event Grid is the platform's general-purpose eventing service. Subscribing to Blob Storage 'BlobCreated' events and routing them to an Azure Function or Container App is the canonical pattern for triggering AI processing on file uploads.
10Which Azure messaging service is designed for ingesting millions of events per second (telemetry, click streams, device data) for downstream AI analysis?
A.Azure Event Hubs
B.Azure Service Bus topics
C.Azure Queue Storage only
D.Azure DNS
Explanation: Azure Event Hubs is the high-throughput event-streaming platform optimized for big-data scenarios such as telemetry and click-stream ingestion. It supports Kafka clients and partitioned consumer groups, making it ideal for feeding AI/ML pipelines at scale.

About the AI-200 Exam

The AI-200 exam validates the skills needed to build, integrate, and operate AI-driven cloud applications on Azure using containerized compute, vector-enabled data services, event-driven AI pipelines, serverless functions, identity-aware application design, secrets management, and distributed observability.

Assessment

Question count not published by the exam provider

Time Limit

120 minutes

Passing Score

700/1000

Exam Fee

Varies by country or region (Microsoft / Pearson VUE)

AI-200 Exam Content Outline

20-25%

Develop containerized solutions on Azure

Build and manage images with Azure Container Registry and Tasks; deploy containers to App Service, Azure Container Apps, and AKS; configure revisions and KEDA scaling; and troubleshoot logs, events, and connectivity.

25-30%

Develop AI solutions by using Azure data management services

Use Azure Cosmos DB for NoSQL, Azure Database for PostgreSQL, vector search and embeddings, change feed processing, indexing and connection optimization, and Azure Managed Redis.

20-25%

Connect to and consume Azure services

Build event- and message-based solutions with Azure Service Bus and Event Grid, and develop Azure Functions with triggers, bindings, configuration, and deployment.

20-25%

Secure, monitor, and troubleshoot Azure solutions

Secure secrets with Azure Key Vault, manage configuration with Azure App Configuration, trace distributed systems with OpenTelemetry, and analyze logs and metrics with KQL.

How to Pass the AI-200 Exam

What You Need to Know

  • Passing score: 700/1000
  • Assessment: Question count not published by the exam provider
  • Time limit: 120 minutes
  • Exam fee: Varies by country or region

Keys to Passing

  • Work through all 218 available questions
  • Review every answer and explanation
  • Track weak areas and revisit them
  • Use our AI tutor for tough concepts

AI-200 Study Tips from Top Performers

1Build at least one end-to-end Azure AI cloud app: Container App + Cosmos DB for NoSQL + Azure OpenAI + Azure AI Search + managed identity + Application Insights, deployed via Bicep and GitHub Actions.
2Practice both vector-enabled patterns the curriculum highlights: pgvector on Azure Database for PostgreSQL and vector search on Cosmos DB for NoSQL. Know when each is preferable.
3Master the Azure Container Apps mental model: environments, revisions, traffic splits, KEDA scalers, jobs, sidecars/Dapr, internal vs external ingress.
4Be fluent with the Azure messaging trio: Service Bus (transactional, ordered), Event Grid (pub/sub, CloudEvents), Event Hubs (high-throughput streaming, Kafka endpoint).
5Memorize keyless authentication patterns: managed identity + RBAC, OIDC federation for GitHub Actions, workload identity for Container Apps and AKS.
6Practice OpenTelemetry instrumentation feeding Application Insights — including W3C trace context propagation, Application Map, and release annotations.
7Know APIM's Azure OpenAI policies (token-based throttling, semantic caching, load balancing), since APIM is the recommended AI gateway.

Frequently Asked Questions

What is the AI-200 exam?

AI-200 is the Microsoft exam for the Azure AI Cloud Developer Associate credential introduced in 2026. It validates the skills needed to build, integrate, monitor, and operate AI-driven cloud applications on Azure across containerized compute, AI-enabled data services, event-driven architectures, identity, secrets, and distributed observability.

How is AI-200 different from AZ-204?

AI-200 is an AI-cloud-development certification built around containerized compute, vector-enabled data services, messaging and eventing, Functions, Key Vault, configuration, and observability. AZ-204 is the separate Developing Solutions for Microsoft Azure exam; candidates should compare the current Microsoft Learn outlines rather than treating one exam as an automatic substitute for the other.

Has Microsoft published an AI-200 skills outline?

Yes. Microsoft's current study guide publishes four measured domains with percentage ranges: containerized solutions (20-25%), AI solutions using Azure data management services (25-30%), connecting to and consuming Azure services (20-25%), and security, monitoring, and troubleshooting (20-25%).

How many questions are on AI-200 and how long do you get?

Microsoft does not publish a fixed AI-200 question count. The current certification page provides 120 minutes to complete the assessment, and Microsoft's study guide states that a scaled score of 700 or greater is required to pass.

How long should I study for AI-200?

Plan for about 80-140 hours over 6-10 weeks depending on prior Azure development experience. Effective preparation includes building at least one production-style AI app: a Container App or Function backend that calls Azure OpenAI with managed identity, persists state to Cosmos DB or PostgreSQL+pgvector, processes events via Service Bus or Event Grid, and is monitored end-to-end via Application Insights. Then complete 100+ practice questions.

Does AI-200 certification expire?

Yes. Microsoft associate certifications expire 12 months after you earn them. You can renew at no cost by passing a free online renewal assessment on Microsoft Learn before the expiration date.