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Azure AI Cloud Developer Associate (AI-200) Crash Course

Published by O'Reilly Media, Inc.

Intermediate content levelIntermediate

Develop AI cloud solutions on Azure

What you’ll learn and how you can apply it

  • Prepare for the AI-200 exam
  • Identify the Azure services used to build and host AI applications
  • Deploy AI applications using Azure container services
  • Store and manage AI application data using Azure Cosmos DB, Azure Database for PostgreSQL, and Azure Managed Redis
  • Protect application secrets and configuration using Azure Key Vault
  • Integrate backend services for AI solutions
  • Implement event-driven AI solutions using Azure Service Bus and Azure Event Grid
  • Monitor and troubleshoot AI applications on Azure

Course description

With Microsoft Azure, developers can design and build AI-powered applications that understand language, process documents, analyze images, generate content, search knowledge sources, and automate business workflows. Azure provides the services, SDKs, and integration options needed to bring AI into real-world applications securely and at scale.

In this crash course, Reza Salehi introduces the key Azure services and development patterns used to build and run AI applications on Azure. You’ll explore how to host your applications using Azure container services; store AI application data in Azure Cosmos DB, Azure Database for PostgreSQL, and Azure Managed Redis; protect application secrets with Azure Key Vault; and implement event-driven AI solutions using Azure Service Bus and Azure Event Grid.

This live event is for you because...

  • You’re starting your journey in AI application development on Azure.
  • You want to understand the Azure services used to host, secure, connect, and support AI applications.
  • You work with, or plan to work with, Azure container services, Azure data services, Key Vault, Service Bus, and Event Grid.
  • You want to prepare for the AI-200 exam and build practical skills for developing AI applications in Azure.

Prerequisites

  • Basic application development experience
  • Familiarity with Azure resources and the Azure portal
  • Basic understanding of containers and cloud services
  • Azure fundamentals-level knowledge (helpful but not required)

Recommended follow-up:

Schedule

The time frames are only estimates and may vary according to how the class is progressing.

Introduction (5 minutes)

  • Presentation: What to expect from this course; about exam AI-200
  • Q&A

Host AI solution containers on Azure (30 minutes)

  • Presentation: Implement Azure Container Registry (ACR) registries, repositories, and artifacts; work with ACR tasks; tag, version, and push container images; deploy container images to Azure App Service
  • Q&A

Deploy AI workloads to Azure Container Apps (25 minutes)

  • Presentation: Understand Azure Container Apps and environments; deploy and manage containers in Azure Container Apps; scale containers in Azure Container Apps with Kubernetes Event-driven Autoscaling; implement performance and cost requirements
  • Q&A
  • Break

Deploy applications to Azure Kubernetes Service (25 minutes)

  • Presentation: Identify the need for Azure Kubernetes Service (AKS); deploy AI applications to AKS; configure secrets, ConfigMaps, and persistent storage; monitor and troubleshoot applications on AKS
  • Q&A

Build AI solutions with Azure Cosmos DB for NoSQL (35 minutes)

  • Presentation: Explore Azure Cosmos DB for AI apps; build queries for Azure Cosmos DB for NoSQL; implement apps with Cosmos DB SDK; build a RAG datastore with Cosmos DB; implement vector search on Azure Cosmos DB for NoSQ; optimize query performance for Azure Cosmos DB for NoSQL
  • Q&A
  • Break

Build AI solutions with Azure Database for PostgreSQL (30 minutes)

  • Presentation: Explore Azure Database for PostgreSQL; build and query with Azure Database for PostgreSQL; implement and optimize vector search with Azure Database for PostgreSQL
  • Q&A

Improve AI solution performance with Azure Managed Redis (15 minutes)

  • Presentation: Explore Azure Managed Redis; implement data operations in Azure Managed Redis; implement event messaging with pub/sub and Redis Streams; implement vector storage in Azure Managed Redis
  • Q&A

Integrate backend services into AI solutions (30 minutes)

  • Presentation: Explore Azure Service Bus; queue and process AI tasks with Azure Service Bus; implement event-driven AI workflows with Event Grid; build serverless AI backends with Azure Functions
  • Q&A
  • Break

Manage secrets and configuration settings for AI solutions (20 minutes)

  • Presentation: Protect application secrets with Azure Key Vault; manage application settings with Azure App Configuration
  • Q&A

Monitor and troubleshoot AI apps on Azure (20 minutes)

  • Presentation: Exploring Application Insights and Log Analytics; monitor an AI application with OpenTelemetry; write basic KQL queries; analyze app telemetry with logs and metrics
  • Q&A

Wrap-up and Q&A (5 minutes)

Your Instructor

Reza Salehi

Reza Salehi is a cloud infrastructure architect and Microsoft Certified Trainer alumnus. He has trained thousands of students in live, on-demand, and in-person courses and is passionate about helping developers and engineers build practical cloud skills. With a background in software development, he also helps organizations adopt modern cloud solutions through consulting and training.

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Skills covered

  • AI-900: Microsoft Azure AI Fundamentals
  • Azure Resource Manager (ARM)
  • AZ-900: Microsoft Azure Fundamentals
  • AZ-204: Developing Solutions for Microsoft Azure