AI-200 Develop AI Cloud Solutions on Azure Training Course

The Microsoft Certified: Azure AI Cloud Developer Associate credential proves you can take an AI solution beyond the model and into production, hosting it in containers, storing embeddings in vector databases, connecting services through messaging, and keeping the whole thing secure and observable. It sits at the associate level of the Azure developer path and is the credential that now defines the role, which is why it carries weight with Australian employers hiring cloud and AI developers.

At Logitrain the AI-200 course includes the official exam fee, the digital course material and mock tests. Every course is backed by our price beat guarantee on a competitor’s advertised price. As an authorised Pearson VUE test centre you can sit the exam at Logitrain, at another Pearson VUE centre, or online. Choose in-person training in Melbourne, Sydney and Brisbane, or live online across Australia, all delivered live in real time with a trainer.

There are no formal prerequisites for this course. Microsoft recommends you come in with programming experience in a language such as Python, JavaScript or C sharp, since the labs and the exam use Python, along with a basic understanding of Azure services and cloud concepts and some familiarity with containers.

If you are new to Azure, start with the AZ-900 Microsoft Azure Fundamentals course to build that base first.

Candidates can achieve this certification by passing the following exam.

• Exam AI-200: Developing AI Cloud Solutions on Azure, Microsoft Certified: Azure AI Cloud Developer Associate

You can book and sit the exam within three months of finishing your course. Sit it at any Pearson VUE test centre, or online through Pearson VUE online proctoring from a private space.

Exam format: around 40 to 60 multiple choice, case study and interactive questions, 120 minutes, with a passing score of 700 on a scale of 100 to 1000.

Your enrolment includes the Logitrain AI-200 Develop AI Cloud Solutions on Azure course material in digital format, mapped to the current exam objectives so you can revise each area after class.

• Build, store, version and manage container images using Azure Container Registry
• Build and run images using Azure Container Registry Tasks
• Deploy containers to Azure App Service with environment variables and secrets
• Deploy and manage applications on Azure Container Apps with revision management
• Scale containers with Kubernetes Event-driven Autoscaling in Container Apps
• Deploy applications to Azure Kubernetes Service using manifest files
• Monitor and troubleshoot workloads on AKS and Container Apps
• Connect to Azure Cosmos DB for NoSQL and run queries with the SDK
• Store and retrieve embeddings and run vector similarity search for semantic retrieval
• Optimise Request Unit consumption using indexing policies and consistency levels
• Implement a change feed processor to handle new and updated items
• Query Azure Database for PostgreSQL and tune pgvector for vector workloads
• Implement retrieval-augmented generation patterns with metadata filtering
• Integrate Azure Managed Redis for caching and vector indexing
• Process back end operations with Azure Service Bus queues, topics and subscriptions
• Build event-driven workflows with Azure Event Grid filters, custom events and retries
• Build serverless APIs with Azure Functions triggers and bindings
• Secure secrets with Azure Key Vault and manage settings with App Configuration
• Trace distributed systems using OpenTelemetry and analyse logs with KQL

• Azure developers
• Cloud application developers
• Back end and full stack developers
• AI application developers
• Software engineers moving into cloud and AI
• DevOps engineers who deploy AI workloads
• Career changers moving into Azure development
• Developers preparing for the Azure AI Cloud Developer Associate certification

• Store and manage container images in Azure Container Registry
• Build and run images using Azure Container Registry Tasks
• Version and manage container images
• Deploy containers to Azure App Service
• Configure App Service environment variables and secrets
• Deploy applications to Azure Container Apps
• Manage environment configuration and revisions in Container Apps
• Implement event-driven scaling with KEDA in Container Apps
• Deploy applications to Azure Kubernetes Service using manifest files
• Configure applications on Azure Kubernetes Service
• Monitor and troubleshoot AKS and Container Apps through logs, events and connectivity
• Connect to Azure Cosmos DB for NoSQL using the SDK
• Build and run queries against Azure Cosmos DB for NoSQL
• Optimise query performance and Request Unit consumption
• Apply indexing policies and consistency levels
• Store and retrieve embeddings in Cosmos DB
• Run vector similarity search for semantic retrieval
• Implement a change feed processor for new and updated items
• Connect and query Azure Database for PostgreSQL with SDKs
• Model schemas and choose appropriate data types and indexing strategies
• Tune pgvector compute overhead and query latency
• Configure compute, memory and storage for vector workloads
• Implement retrieval-augmented generation patterns with metadata filtering
• Optimise connections to improve throughput and reduce latency
• Implement Azure Managed Redis caching, expiration and invalidation
• Implement vector indexing in Azure Managed Redis for similarity search
• Queue and process back end operations with Azure Service Bus
• Handle dead-letter queues, messages, topics and subscriptions
• Implement event-driven workflows with Azure Event Grid
• Configure Event Grid filters, custom events and retries
• Build serverless APIs with Azure Functions triggers and bindings
• Configure and deploy function apps
• Secure secrets with Azure Key Vault including rotation and retrieval
• Store and retrieve application settings with Azure App Configuration
• Trace distributed systems using OpenTelemetry SDKs
• Write KQL queries to analyse logs and metrics

• AZ-900 Microsoft Azure Fundamentals: the entry point to Azure and the best starting course if you are new to the cloud.
• AI-901 Microsoft Azure AI Fundamentals: a plain grounding in AI on Azure before associate level work.
• AI-103 Azure AI Apps and Agents: the companion associate course focused on the AI services and agents themselves rather than the back end.
• AZ-104 Microsoft Azure Administrator: for those who want the administration side of Azure alongside development.
• AZ-305 Designing Microsoft Azure Infrastructure Solutions: the architect level step for designing Azure solutions.
• Artificial Intelligence Job Ready Program: training, certifications, internship and career counselling for those aiming to land an AI role.
• Microsoft Azure courses: the full range of Azure training at Logitrain.

Got a team to train? Logitrain can deliver the AI-200 Develop AI Cloud Solutions on Azure course in house at your premises anywhere in Australia, with the same trainer, course material, mock test and official exam fee as the public courses. It suits teams who want everyone trained together on dates that suit the business.

What is the AI-200 course?

It is the current associate level Azure developer course, teaching you to build, secure and monitor the back end of AI applications on Microsoft Azure. It leads to the Microsoft Certified: Azure AI Cloud Developer Associate certification.

Is the exam fee included in the course?

Yes. The official exam fee is included at Logitrain, and you can sit the exam within three months of finishing your course at our Pearson VUE test centre, at another Pearson VUE centre, or online.

What replaced AZ-204?

Microsoft retired the AZ-204 exam and the Azure Developer Associate certification on 31 July 2026. AI-200 and the Azure AI Cloud Developer Associate certification are the replacement path, with a stronger focus on AI workloads.

Are there prerequisites for AI-200?

There are no formal prerequisites. Microsoft recommends programming experience in a language such as Python, a basic understanding of Azure and cloud concepts, and some familiarity with containers.

How long is the AI-200 course?

The course runs over five days full time, or five weeks part time if you study in the evenings or on weekends.

Where can I take the AI-200 course?

In-person in Melbourne, Sydney, Brisbane, Adelaide, Perth and Canberra, plus live online across Australia, all delivered live in real time with a trainer.

Should I do AI-200 or AI-103 first?

They cover different sides of the same field. AI-200 is about building and running the back end that AI applications depend on, while AI-103 focuses on the Azure AI services and agents. Choose the one that matches your role, or take both to cover the full picture.