Develop AI cloud solutions on Azure | AI-200
Skip to main Content

Develop AI cloud solutions on Azure (AI-200)

  • Course Code M-AI200
  • Duration 5 days

Course Delivery

Company Event Price

Please call

Request Group Training Add to Cart

Course Delivery

This course is available in the following formats:

  • Company Event

    Event at company

  • Public Classroom

    Traditional Classroom Learning

  • Virtual Learning

    Learning that is virtual

Request this course in a different delivery format.

Course Overview

Top

Create, monitor, and troubleshoot AI solutions on Microsoft Azure.

AI‑200 validates the skills required to design, build, and operate cloud‑native AI solutions on Microsoft Azure.It focuses on integrating Azure AI services into scalable applications using containers, serverless compute, event‑driven architectures, and vector‑enabled data stores.Learners gain hands‑on experience securing, monitoring, and optimizing AI workloads across the full application lifecycle.

Company Events

These events can be delivered exclusively for your company at our locations or yours, specifically for your delegates and your needs. The Company Events can be tailored or standard course deliveries.

Course Schedule

Top

Target Audience

Top
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

Top

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.

Course Content

Top

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

Course Prerequisites

Top

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.

Test Certification

Top

None

Follow on Courses

Top

None