The AI-200 exam: Developing AI Cloud Solutions on Azure is designed for developers who build and implement AI solutions on Microsoft Azure. The exam focuses on back-end AI services, containerized applications, Azure data management, messaging, security, monitoring, and troubleshooting. Passing the exam earns the Microsoft Certified: Azure AI Cloud Developer Associate certification.
What Is the AI-200 Exam?
AI-200 is an intermediate-level Microsoft certification exam for developers responsible for implementing AI cloud solutions throughout the development lifecycle, including design, development, deployment, security, monitoring, and troubleshooting. Candidates should be comfortable with Python, Azure SDKs, data services, messaging, eventing, vector databases, and containerized applications.
AI-200 Exam Skills Measured
1. Develop Containerized Solutions on Azure — 20–25%
Important topics include:
- Azure Container Registry
- Container images
- Azure Container Registry Tasks
- Azure App Service
- Azure Container Apps
- Environment variables and secrets
- Revision management
- KEDA event-driven scaling
- Azure Kubernetes Service (AKS)
- Container monitoring and troubleshooting
2. Develop AI Solutions Using Azure Data Management Services — 25–30%
This is one of the largest AI-200 exam areas.
Focus on:
- Azure Cosmos DB for NoSQL
- SDK connections and queries
- Indexing policies
- Request Unit optimization
- Embeddings
- Vector similarity search
- Semantic retrieval
- Change feed processing
- Azure Database for PostgreSQL
- pgvector
- RAG patterns
- Azure Managed Redis
- Caching and invalidation
3. Connect to and Consume Azure Services — 20–25%
Study how AI applications communicate with Azure services.
Important topics include:
- Azure Service Bus
- Queues
- Topics and subscriptions
- Dead-letter queues
- Azure Event Grid
- Event-driven architecture
- Custom events
- Retry mechanisms
- Azure Functions
- Serverless APIs
- Triggers and bindings
4. Secure, Monitor, and Troubleshoot Azure Solutions — 20–25%
Security and observability are important for production AI applications.
Focus on:
- Azure Key Vault
- Secret rotation and retrieval
- Azure App Configuration
- Application configuration
- OpenTelemetry
- Distributed tracing
- KQL queries
- Logs and metrics
- Troubleshooting Azure applications
Key AI-200 Topics to Study
Azure Containers and Application Hosting
Learn how to build, store, deploy, and manage containerized applications by using Azure services.
Important services include:
- Azure Container Registry
- Azure Container Apps
- Azure Kubernetes Service
- Azure App Service
Understanding container deployment, scaling, revisions, environment configuration, and monitoring is essential.
Vector Databases and AI Data
Modern AI applications frequently use embeddings and vector search.
Candidates should understand:
- Embeddings
- Vector indexing
- Similarity search
- Semantic retrieval
- Vector databases
- RAG architectures
- Metadata filtering
AI-200 covers using services such as Azure Cosmos DB for NoSQL and Azure Database for PostgreSQL for AI data workloads.
Azure Messaging and Eventing
AI cloud applications often use asynchronous and event-driven architectures.
Study:
- Azure Service Bus
- Queues
- Topics
- Subscriptions
- Event Grid
- Event filters
- Custom events
- Retries
- Dead-letter queues
Azure Functions
Azure Functions can be used to build serverless APIs and process AI application workloads.
Focus on:
- Function apps
- Triggers
- Bindings
- API development
- Deployment
- Serverless architecture
Security
Secure application development is important for cloud AI solutions.
Study:
- Azure Key Vault
- Secret management
- Secret rotation
- Azure App Configuration
- Secure configuration practices
Monitoring and Troubleshooting
Production applications must be observable and reliable.
Focus on:
- OpenTelemetry
- Distributed tracing
- Logs
- Metrics
- KQL
- Application monitoring
- Troubleshooting
How to Prepare for the AI-200 Exam
Step 1: Learn Azure Development Fundamentals
Start by understanding the Azure services used to build and deploy modern cloud applications.
Focus on:
- Azure resources
- SDKs
- Python
- APIs
- Cloud application architecture
Step 2: Practice Containerized Applications
Build practical projects using containers.
Learn how to:
- Create container images
- Store images in Azure Container Registry
- Deploy applications
- Configure environment variables
- Manage scaling
Step 3: Learn AI Data Management
Spend significant time understanding vector data.
Practice:
- Creating embeddings
- Storing vectors
- Performing similarity searches
- Building basic RAG workflows
Step 4: Study Messaging and Event-Driven Systems
Learn how Azure services communicate asynchronously.
Practice with:
- Azure Service Bus
- Event Grid
- Azure Functions
Step 5: Learn Security and Monitoring
Understand how to secure secrets and monitor distributed applications.
Focus on:
- Key Vault
- App Configuration
- OpenTelemetry
- Logs and metrics
- KQL queries
Step 6: Build Hands-On Projects
Practical experience can help reinforce the exam objectives.
Consider building:
- A containerized AI application
- A RAG application with vector search
- An event-driven AI workflow
- A serverless AI API
- A monitored Azure AI application
Microsoft recommends training and hands-on experience as part of AI-200 preparation.
AI-200 Study Plan
Week 1: Azure Containers
Study:
- Container basics
- Azure Container Registry
- Container Apps
- AKS
- App Service
Week 2: AI Data and Vector Search
Focus on:
- Azure Cosmos DB
- PostgreSQL
- Embeddings
- Vector search
- Semantic retrieval
- RAG
Week 3: Messaging and Serverless Development
Study:
- Azure Service Bus
- Event Grid
- Azure Functions
- Event-driven architecture
Week 4: Security, Monitoring and Revision
Focus on:
- Key Vault
- App Configuration
- OpenTelemetry
- KQL
- Logs and metrics
- Practice questions
AI-200 Practice Questions
Question 1
Which Azure service is used to store and manage container images?
A. Azure Functions
B. Azure Container Registry
C. Azure Event Grid
D. Azure Key Vault
Answer: B. Azure Container Registry
Question 2
What is the primary purpose of vector similarity search?
A. To compress application files
B. To find semantically similar data
C. To encrypt all database records
D. To manage user passwords
Answer: B. To find semantically similar data
Question 3
Which Azure service is designed for enterprise messaging using queues, topics, and subscriptions?
A. Azure Service Bus
B. Azure Key Vault
C. Azure App Service
D. Azure Monitor
Answer: A. Azure Service Bus
Question 4
Which service can securely store application secrets?
A. Azure Event Grid
B. Azure Container Registry
C. Azure Key Vault
D. Azure Functions
Answer: C. Azure Key Vault
Question 5
What can OpenTelemetry help developers implement?
A. Distributed tracing
B. Image editing
C. Database deletion
D. Password generation
Answer: A. Distributed tracing
AI-200 FAQs
What is the AI-200 exam?
AI-200 is Microsoft's Developing AI Cloud Solutions on Azure exam. It focuses on developing AI cloud solutions using Azure services.
What certification can I earn by passing AI-200?
Passing AI-200 earns the Microsoft Certified: Azure AI Cloud Developer Associate certification.
What is the AI-200 exam level?
The certification is classified by Microsoft as intermediate and is targeted toward developers.
How long is the AI-200 exam?
Microsoft currently lists 120 minutes for the assessment.
What programming language should I know for AI-200?
Microsoft lists Python programming as one of the expected skills for candidates.
Does AI-200 cover containers?
Yes. Containerized Azure solutions, including Container Registry, Container Apps, App Service, and AKS, are covered in the exam.
Does AI-200 cover vector databases?
Yes. The exam covers embeddings, vector similarity search, semantic retrieval, and vector workloads using Azure data services.
Does AI-200 cover RAG?
Yes. Retrieval-augmented generation patterns and semantic retrieval are included in the AI data management objectives.
Does AI-200 cover Azure Functions?
Yes. Candidates should understand how to build serverless APIs using Azure Functions, including triggers and bindings.
What score is required to pass AI-200?
Microsoft's study guide states that a score of 700 or greater is required to pass.
Conclusion
The AI-200 exam is designed for developers who want to build modern AI cloud solutions on Azure. The most important areas to study are containerized applications, AI data management, vector databases, embeddings, RAG, Azure messaging, serverless APIs, security, monitoring, and troubleshooting.
A strong preparation strategy should combine Microsoft Learn resources with practical Azure projects. Building containerized and event-driven AI applications can help you gain the hands-on knowledge required for the exam.
Written By:Sudheer Kumar
Published on: 02/09/2026
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