Develop AI Cloud Solutions on Azure

This course teaches developers how to create, monitor, and troubleshoot AI solutions on Microsoft Azure. Students will learn how to implement Azure compute and containerization patterns to host applications, build serverless APIs with Azure Functions, and integrate services using event‑driven and message‑based architectures such as Azure Service Bus and Event Grid.

The course also covers working with Azure data services that support AI workloads, including designing and querying solutions with Cosmos DB for NoSQL, Azure Database for PostgreSQL with pgvector, and Azure Managed Redis for caching, streaming, and vector search. By the end of the course, developers will be able to connect services, orchestrate AI workflows, and build secure, scalable, and observable AI‑driven applications on Azure.

Audience Profile

This course is designed for developers who build backend and AI‑driven applications on Azure and need practical skills in containerized compute, data services for AI, event‑driven workflows, and application security and monitoring.

Course Objectives

In this course, students will learn how to implement Azure compute and containerization patterns to host applications, build serverless APIs with Azure Functions, and integrate services using event driven and message based architectures such as Azure Service Bus and Event Grid. The course also covers working with Azure data services that support AI workloads, including designing and querying solutions with Cosmos DB for NoSQL, Azure Database for PostgreSQL with pgvector, and Azure Managed Redis for caching, streaming, and vector search. By the end of the course, developers will be able to connect services, orchestrate AI workflows, and build secure, scalable, and observable AI driven applications on Azure.

Pre-requisites

Learners should have hands on experience with Azure fundamentals and practical knowledge of building cloud applications using containers, serverless compute, and event driven architectures, along with familiarity with core AI concepts and integrating Azure AI services into applications.

What will you learn in AI-200 training?

Module 1: Implement container application hosting on Azure

• Store and manage containers in Azure Container Registry.

• Deploy containers to Azure App Service.

Module 2: Deploy and manage apps on Azure Container Apps

• Deploy containers to Azure Container Apps.

• Manage containers in Azure Container Apps.

• Scale containers in Azure Container Apps.

Module 3: Deploy and monitor applications on Azure Kubernetes Service

• Deploy applications to Azure Kubernetes Service.

• Configure applications on Azure Kubernetes Service.

• Monitor and troubleshoot applications on Azure Kubernetes Service.

Module 4: Develop AI solutions with Azure Cosmos DB for NoSQL

• Build queries for Azure Cosmos DB for NoSQL.

• Implement vector search on Azure Cosmos DB for NoSQL.

• Optimize query performance for Azure Cosmos DB for NoSQL.

Module 5: Develop AI solutions with Azure Database for PostgreSQL

• Build and query with Azure Database for PostgreSQL.

• Implement vector search with Azure Database for PostgreSQL.

• Optimize vector search in Azure Database for PostgreSQL.

Module 6: Enhance AI solutions with Azure Managed Redis

• Implement data operations in Azure Managed Redis.

• Implement event messaging with Azure Managed Redis.

• Implement vector storage in Azure Managed Redis.

Module 7: Integrate backend services for AI solutions

• Queue and process AI operations with Azure Service Bus.

• Develop event-driven AI workflows with Azure Event Grid.

• Build serverless AI backends with Azure Functions.

Module 8: Manage application secrets and configuration for AI solutions

• Manage application secrets with Azure Key Vault.

• Manage application settings with Azure App Configuration.

Module 9: Observe and troubleshoot apps on Azure

• Instrument an app with OpenTelemetry.

• Analyze app telemetry with logs and metrics.

Assessed on this exam

• Develop containerized solutions on Azure.

• Develop AI solutions by using Azure data management services.

• Connect to and consume Azure services.

• Secure, monitor, troubleshoot Azure solutions.