Develop AI Cloud Solutions on Azure (AI-200)

Course 8774 Advantage Plan Course

  • Duration: 5 days
  • Exam Voucher: Yes
  • Language: English
  • Level: Intermediate

Learn to develop, deploy, integrate, and monitor AI-powered cloud applications using Microsoft Azure. This course provides developers with practical skills in containerized application hosting, serverless computing, event-driven architectures, and Azure data services that support AI workloads.

Explore Azure Container Apps, Azure Kubernetes Service, Azure Functions, Cosmos DB, PostgreSQL, and Azure Managed Redis while learning to build secure, scalable, and reliable AI cloud solutions.

Develop AI Cloud Solutions on Azure (AI-200) Delivery Methods

  • In-Person

  • Online

  • Upskill your whole team by bringing Private Team Training to your facility.

Develop AI Cloud Solutions on Azure (AI-200) Training Information

  • In this course, you will learn how to:

    • Deploy and manage containerized applications using Azure Container Apps and Azure Kubernetes Service.
    • Develop scalable AI application backends using Azure data services.
    • Integrate cloud services using serverless and event-driven architectures.
    • Secure application secrets, identities, and configuration.
    • Monitor, troubleshoot, and optimize AI cloud applications.

    Who Should Attend

    This course is designed for software developers, cloud application developers, and technical professionals responsible for building and maintaining AI-powered applications on Microsoft Azure. It is particularly beneficial for developers working with backend services, containerized applications, cloud data solutions, and distributed architectures.

    Prerequisites

    Participants should have:

    • Experience developing applications using a programming language such as C#, Python, or JavaScript.
    • Familiarity with fundamental Azure services and cloud computing concepts.
    • Basic understanding of APIs, databases, and application development.
    • Familiarity with containers and distributed application concepts is beneficial.

Develop AI Cloud Solutions on Azure (AI-200) Training Outline

Implement Container Application Hosting on Azure

Explore how to package, store, and deploy containerized applications on Azure. Learn the fundamentals of container hosting and managing container images to support scalable cloud solutions.

 

Objectives:

  • Understand containerization concepts and Azure hosting options.
  • Create and manage container images.
  • Store and manage images using Azure Container Registry.
  • Deploy containerized applications to Azure environments.

 

Deploy and Manage Apps on Azure Container Apps

Learn to deploy and manage applications using Azure Container Apps, including configuration, scaling, and application lifecycle management.

 

Objectives:

  • Understand Azure Container Apps architecture and capabilities.
  • Deploy and configure containerized applications.
  • Configure application networking and environment settings.
  • Manage application scaling, revisions, and updates.

 

Deploy and Monitor Applications on Azure Kubernetes Service

Explore Azure Kubernetes Service (AKS) for orchestrating containerized applications. Learn to deploy workloads, configure Kubernetes resources, and monitor application performance.

 

Objectives:

  • Understand Kubernetes architecture and core AKS components.
  • Deploy and manage applications on AKS.
  • Configure Kubernetes workloads and networking.
  • Monitor and troubleshoot containerized applications.

 

 

 

Develop AI Solutions with Azure Cosmos DB for NoSQL

Discover how Azure Cosmos DB supports AI-driven applications through scalable, flexible data storage and querying capabilities.

 

Objectives:

  • Understand Azure Cosmos DB for NoSQL architecture and capabilities.
  • Design databases, containers, and data models.
  • Develop applications that read, write, and query data.
  • Optimize data access and performance for AI workloads.

 

Develop AI Solutions with Azure Database for PostgreSQL

Learn to use Azure Database for PostgreSQL to manage relational and vector data supporting AI applications, including similarity searches with pgvector.

 

Objectives:

  • Understand Azure Database for PostgreSQL capabilities.
  • Configure and manage PostgreSQL databases on Azure.
  • Store and query vector data using pgvector.
  • Implement vector similarity searches for AI applications.

 

Enhance AI Solutions with Azure Managed Redis

Explore how Azure Managed Redis improves application performance through caching, messaging, and vector data capabilities.

 

Objectives:

  • Understand Azure Managed Redis features and use cases.
  • Implement caching to improve application performance.
  • Explore Redis messaging and streaming capabilities.
  • Use Redis vector search capabilities in AI applications.

 

 

 

Integrate Backend Services for AI Solutions

Learn to connect cloud application components using Azure integration services, serverless computing, and event-driven architectures.

 

Objectives:

  • Develop serverless application components using Azure Functions.
  • Integrate services using Azure Service Bus.
  • Implement event-driven workflows using Azure Event Grid.
  • Design reliable communication between distributed application components.
  • Connect backend services to support AI application workflows.

 

Manage Application Secrets and Configuration for AI Solutions

Learn to protect sensitive application information and securely manage configuration settings across Azure environments.

 

Objectives:

  • Secure application secrets and credentials using Azure Key Vault.
  • Manage application settings using Azure App Configuration.
  • Implement secure access to application resources.
  • Apply configuration and secrets management best practices.

 

Observe and Troubleshoot Apps on Azure

Explore Azure monitoring and diagnostic tools used to track application health, identify performance issues, and troubleshoot cloud solutions.

 

Objectives:

  • Understand Azure Monitor and application observability.
  • Collect and analyze application logs and metrics.
  • Monitor application performance using Application Insights.
  • Diagnose and troubleshoot application failures and performance issues.

 

Certification

This course aligns with Exam AI-200: Developing AI Cloud Solutions on Azure, associated with the Microsoft Certified: Azure AI Cloud Developer Associate certification.

 

Completing this course provides training related to the certification exam but does not guarantee certification.

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Develop AI Cloud Solutions on Azure (AI-200) Training FAQs

You'll learn to build, deploy, integrate, secure, and monitor AI-powered applications using Microsoft Azure. The course covers containerized applications, serverless computing, Azure data services, event-driven architectures, and application monitoring.

This course is designed for software developers, cloud application developers, and IT professionals who build or support AI-driven applications on Azure. It is particularly useful for developers working with backend services, cloud infrastructure, and distributed applications.

You'll work with Azure Container Apps, Azure Kubernetes Service (AKS), Azure Functions, Azure Cosmos DB, Azure Database for PostgreSQL, Azure Managed Redis, Azure Service Bus, Event Grid, Azure Key Vault, and Azure monitoring services.

Yes. This intermediate-level course is best suited for participants with programming experience and a basic understanding of Azure, APIs, databases, and cloud application development. Familiarity with containers and distributed applications is helpful.

No. While the course supports AI application development, its primary focus is building the cloud infrastructure, backend services, data integrations, and monitoring capabilities needed to run AI-powered applications on Azure.

Yes. The course aligns with Exam AI-200, associated with the Microsoft Certified: Azure AI Cloud Developer Associate certification. It covers relevant technical skills, although additional study and hands-on practice may be needed to prepare for the exam.