Microsoft AI-200 Certification

The free study guide for Azure AI Cloud Developers

Nine modules of concise notes, code examples, cheatsheets, and exam tips — mapped to Course AI-200T00-A. No login, no paywall.

Exam structure

Four skill domains

Microsoft weights each domain differently. Allocate study time in proportion to the weight rather than to personal interest — Domain 2 carries the most marks and contains the material least likely to be covered by prior Azure experience.

  1. Domain 1

    Develop Containerized Solutions on Azure

    20–25%
  2. Domain 2 Highest weight

    Develop AI Solutions by Using Azure Data Management Services

    25–30%
  3. Domain 3

    Connect to and Consume Azure Services

    20–25%
  4. Domain 4

    Secure, Monitor, and Troubleshoot Azure Solutions

    20–25%

Course content

Nine study modules

Each module maps to Course AI-200T00-A and includes concise notes, diagrams, code examples, and exam tips.

Module 1 20–25%

Implement Container Application Hosting on Azure

Build, store, version, and manage container images using Azure Container Registry. Build and run images with ACR Tasks. Deploy containers to Azure App Service with environment variables and secrets.

Azure Container RegistryACR TasksAzure App Service
6 topics Study now →
Module 2 20–25%

Deploy and Manage Apps on Azure Container Apps

Deploy applications to Azure Container Apps with environment configuration and revision management. Implement event-driven scaling with KEDA. Deploy and manage apps on AKS using manifest files.

Azure Container AppsKEDAAKS
5 topics Study now →
Module 3 20–25%

Deploy and Monitor Applications on Azure Kubernetes Service

Deploy and manage workloads on AKS using kubectl and manifest files. Configure node pools, networking with Azure CNI, and monitor with Container Insights and KQL.

Azure Kubernetes ServicekubectlHelm
5 topics Study now →
Module 4 25–30%

Develop AI Solutions with Azure Cosmos DB for NoSQL

Connect to Cosmos DB using the SDK and run queries. Optimize RU consumption with indexing policies and consistency levels. Store embeddings and execute vector similarity search. Implement change feed processor.

Azure Cosmos DBDiskANNChange Feed
7 topics Study now →
Module 5 25–30%

Develop AI Solutions with Azure Database for PostgreSQL

Connect and query PostgreSQL Flexible Server with SDKs. Model schemas and implement indexing strategies. Configure resources for vector workloads. Run vector similarity search and implement RAG patterns.

Azure Database for PostgreSQLpgvectorHNSW
6 topics Study now →
Module 6 25–30%

Enhance AI Solutions with Azure Managed Redis

Implement Azure Managed Redis data operations including caching, expiration, and invalidation. Implement vector indexing to enable similarity search for semantic caching and RAG.

Azure Managed RedisRediSearchVector Index
4 topics Study now →
Module 7 20–25%

Integrate Backend Services for AI Solutions

Queue and process back-end operations with Azure Service Bus including dead-letter queue handling. Implement event-driven workflows with Event Grid. Build serverless APIs with Azure Functions triggers and bindings.

Azure Service BusAzure Event GridAzure Functions
6 topics Study now →
Module 8 20–25%

Manage Application Secrets and Configuration for AI Solutions

Secure secrets by using Azure Key Vault, including rotation and retrieval. Store and retrieve app configuration using Azure App Configuration. Use Key Vault references and feature flags.

Azure Key VaultAzure App Configuration
5 topics Study now →
Module 9 20–25%

Observe and Troubleshoot Apps on Azure

Trace distributed systems by using OpenTelemetry SDKs. Write KQL queries to analyze logs and metrics. Configure Application Insights, set up alerts, and build observability pipelines.

OpenTelemetryKQLAzure Monitor
5 topics Study now →

Practice

Test yourself

Untimed practice, a timed mock exam, and the full question bank — all on one page.

Start with Module 1

Begin with Azure Container Registry, work through all nine modules, then use the exam preparation page for final review the night before your exam.

Frequently Asked Questions

What is the AI-200 exam? +

The AI-200 (Developing AI Cloud Solutions on Azure) is a Microsoft certification exam that validates your ability to design, build, and deploy AI-powered applications on Azure. It replaces the AZ-204 exam (retiring July 31, 2026) and focuses on containers, AI data services, event-driven architectures, and observability.

Is the AI-200 harder than AZ-204? +

The AI-200 covers similar compute and messaging topics as AZ-204, but adds AI-specific data services (Cosmos DB vector search, pgvector, Redis vector search) and modern observability (OpenTelemetry, KQL). If you're already familiar with AZ-204, the new AI data services are the main areas to focus on.

How should I prepare for the AI-200? +

Use this free study guide to cover all 9 learning paths. Each module includes concise notes, code examples, animated diagrams, and exam tips. Supplement with hands-on Azure practice and the official Microsoft Learn training course (AI-200T00-A).

What score do I need to pass the AI-200? +

You need a minimum score of 700 out of 1000 to pass. The exam has approximately 40-60 questions and you have 100 minutes to complete it. Question types include multiple choice, multiple response, drag-and-drop, and case studies.

Frequently asked questions

Is this study guide really free? +

Yes. All 9 modules, cheatsheets, exam tips, and the revision page are free with no account required. We offer an optional paid Question Pack (400 practice questions) and Mock Exam Pack (700 questions).

What is the AI-200 exam? +

Microsoft AI-200 (Azure AI Cloud Developer Associate) is the replacement for the retiring AZ-204 exam. It tests your ability to design and implement containerized AI solutions, AI data services, event-driven pipelines, and secure, monitored Azure deployments.

How long does it take to prepare for AI-200? +

Most candidates with an Azure background (AZ-204 or equivalent experience) need 3–5 weeks studying 1–2 hours per day. Candidates new to Azure containers and databases should plan for 6–8 weeks.

What topics does AI-200 cover? +

Four domains: (1) Containerized solutions — ACR, AKS, Container Apps. (2) AI data solutions — Cosmos DB vector search, PostgreSQL/pgvector, Redis. (3) Event-driven solutions — Service Bus, Event Grid, Event Hubs, Functions. (4) Security and monitoring — Key Vault, RBAC, Azure Monitor, KQL.

How is this guide different from Microsoft Learn? +

Microsoft Learn is comprehensive but dense. This guide is exam-focused — each module is distilled to what actually appears in the exam, with clear explanations of why answers are correct, not just what the answer is.

Do I need to code to pass AI-200? +

The exam is scenario-based multiple choice, not a coding test. However, understanding code patterns (ARM/Bicep, Kubernetes YAML, Python SDK calls) helps you reason through scenario questions faster.