Is AI-200 Replacing AZ-204?

Yes. Microsoft has announced the retirement of AZ-204 on July 31, 2026, and AI-200 is positioned as the next-generation Azure developer certification focused on AI-native cloud application development.

Why Is AI-200 Important for Azure AI and Cloud Developers?

Learn how to develop enterprise-grade AI solutions on Azure
Gain hands-on experience with containerized AI applications
Understand vector databases and semantic search implementations
Build scalable AI back-end architectures using Azure services
Learn modern AI integration patterns such as RAG and event-driven systems
Develop skills in Azure Kubernetes Service (AKS) and Azure Container Apps
Implement monitoring, security, and troubleshooting for AI workloads
Prepare for emerging AI Cloud Developer and Generative AI Engineer roles
Validate your expertise with Microsoft’s new role-based AI certification

What Skills Will You Gain from the AI-200 Certification?

Designing and implementing AI application architectures on Azure
Building containerized AI applications using Azure services
Working with - Azure Container Apps, Kubernetes Service (AKS), Container Registry (ACR)
Implementing scalable AI workloads using - Kubernetes Event-driven Autoscaling (KEDA), Azure Functions, Azure Event Grid, Azure Service Bus
Developing AI solutions using: Azure Cosmos DB for NoSQL, Azure Database for PostgreSQL, and Azure Managed Redis
Implementing - Vector databases, Embeddings storage, Vector similarity search, Semantic retrieval, and Retrieval-Augmented Generation (RAG)
Integrating AI applications with Azure SDKs and third-party SDKs
Managing secrets and configurations using - Azure Key Vault, Azure App Configuration
Monitoring and troubleshooting distributed AI applications
Writing KQL queries for logs and metrics analysis
Implementing distributed tracing using OpenTelemetry
Working with Python-based AI development and integrations

What Topics Are Covered in the AI-200 Exam?

Develop containerized solutions on Azure (20–25%)
Develop AI solutions by using Azure data management services (25–30%)
Connect to and consume Azure services (20–25%)
Secure, monitor, and troubleshoot Azure solutions (20–25%)

What Does the AI-200 Training Course Include?

Implement container application hosting on Azure
Deploy and manage apps on Azure Container Apps
Deploy and monitor applications on Azure Kubernetes Service (AKS)
Develop AI solutions with Azure Cosmos DB for NoSQL
Develop AI solutions with Azure Database for PostgreSQL
Enhance AI solutions with Azure Managed Redis
Integrate backend services for AI solutions
Secure and monitor AI workloads on Azure
Implement scalable AI event-driven architectures

Key AI-200 Training Features for Azure AI Developers

Role-based AI developer certification
Focused on real-world AI application development
Covers Generative AI and vector database integrations
Hands-on containerized AI deployment scenarios
Covers AKS, Container Apps, Cosmos DB, PostgreSQL, Redis, and Azure Functions
Includes event-driven AI architectures
Aligned with latest Azure AI cloud development practices
Strong emphasis on monitoring, troubleshooting, and scalability

What Experience Is Recommended Before Taking AI-200?

Experience with Python & Familiarity with Azure services and Azure SDKs
Understanding of container technologies and Kubernetes
Basic knowledge of AI workloads and Generative AI concepts
Familiarity with REST APIs and cloud-native applications
Understanding of distributed systems and monitoring

Are There Any Prerequisites for AI-200 Certification?

There are no mandatory prerequisites for this certification. However, the following knowledge is highly recommended:

Basic Azure cloud knowledge
Python development experience
Familiarity with containers and Kubernetes
Understanding of AI concepts and embeddings
Awareness of event-driven architectures
Basic database and API integration knowledge

Who Should Pursue the AI-200 Certification?

Cloud Developers
AI Developers
Azure Developers
Generative AI Engineers
Backend Engineers building AI applications
Developers working with vector databases and RAG systems
AI Solution Architects
Developers transitioning into AI engineering roles

What Are the Benefits of the AI-200 Certification?

Build expertise in enterprise AI solution development
Learn modern Azure AI development practices
Gain hands-on experience with scalable AI architectures
Understand vector search and semantic retrieval systems
Develop cloud-native AI engineering skills
Prepare for advanced AI engineering and cloud developer roles
Validate your Azure AI development expertise with Microsoft

What Career Opportunities Are Available After AI-200?

After completing this certification, you can explore roles such as:

Azure AI Cloud Developer
Generative AI Engineer
AI Solutions Developer
Cloud AI Engineer
Backend AI Developer
AI Platform Engineer
Azure Kubernetes AI Engineer
AI Integration Specialist

It also helps prepare you for advanced AI and cloud engineering paths involving:

MLOps Engineering
Enterprise AI Architecture
Agentic AI Development
Distributed AI Systems Engineering