Search Results

Further Information

• AI-102: Course Overview

  As a Microsoft Azure AI engineer, you build, manage, and deploy AI solutions that leverage Azure AI.

  Your responsibilities include participating in all phases of AI solutions development, including:

  • Requirements definition and design
  • Development
  • Deployment
  • Integration
  • Maintenance
  • Performance tuning
  • Monitoring

  You work with solution architects to translate their vision. You also work with data scientists, data engineers, Internet of Things (IoT) specialists, infrastructure administrators, and other software developers to:

  • Build complete and secure end-to-end AI solutions.
  • Integrate AI capabilities in other applications and solutions.

  As an Azure AI engineer, you have experience developing solutions that use languages such as:

  • Python
  • C#

• AI-102: Course Modules

  Module 1: Get started with Azure AI Services

  Module 2: Develop generative AI apps in Azure

  Module 3: Develop Generative AI solutions with Azure OpenAI in Foundry Models

  Module 4: Develop AI agents on Azure

  Module 5: Develop natural language solutions in Azure

  Module 6: Develop computer vision solutions in Azure

  Module 7: Implement knowledge mining with Azure AI Search

• AI-102: Course Objectives

  By the end of this course, you should be able to use Representational State Transfer (REST) APIs and SDKs to build secure image processing, video processing, natural language processing, knowledge mining, and generative AI solutions on Azure.

  You should:

  • Understand the components that make up the Azure AI portfolio and the available data storage options.
  • Be able to apply responsible AI principle.

• AI-102: Prerequisites

  This course is ideal for software engineers and developers who are interested in building, managing, and deploying AI solutions on Azure. Attendees should have experience with C# or Python and be familiar with using REST-based APIs for AI applications.