AI-100 Exam Preparation - Introduction
AI-100 Exam Preparation - Introduction

This introduction to the AI-100 Exam Preparation: Designing and Implementing an Azure AI Solution learning path gives an overview of the requirements for the Microsoft AI-100 exam and how they will be covered.

The three major subject areas are:

  • Analyzing solution requirements
  • Designing AI solutions
  • Implementing and monitoring AI solutions

Hello and welcome to Designing and Implementing an Azure AI Solution. The focus of this learning path is to prepare you for Microsoft’s AI-100 exam, but even if you’re not going to take the exam, this learning path will help you get started on your way to becoming an Azure AI engineer.

My name’s Guy Hummel and I’m a Microsoft Certified Azure Solutions Architect and AI Engineer.

The AI-100 exam tests your knowledge of three subject areas: analyzing solution requirements, designing AI solutions, and implementing and monitoring AI solutions. Really, what all of this boils down to, though, is how to use Azure Cognitive Services and other related services to create an artificial intelligence solution.

The Cognitive Services suite is a collection of pre-built AI components that you can use without having to build your own machine learning models. For example, if you need to build an application that can identify famous people in pictures, you don’t have to go through the work of training a machine learning model to do it. Instead, you can just use the Computer Vision API, which is one of the tools in the Cognitive Services suite.

But before we dive into how to use Cognitive Services, we’re going to start this learning path by giving you an overview of Azure services. This is an important first step because you need to know what other Azure services to add to build a complete solution, including areas like storage, security, orchestration, and monitoring.

Once you have that foundation, we’ll dig into how to use the various Cognitive Services. They’re divided into five categories: decision, language, speech, vision, and web search. For example, we’ll show you how to use the Speech-to-Text API to transcribe an audio file.

Next, we’ll show you how to build a chatbot using the Azure Bot Service. This isn’t technically part of Cognitive Services, but it’s similar because it’s a tool for building a specific type of AI solution. Probably the most common use for chatbots is customer support.

Finally, we’ll show you how to tie all of the components together into pipelines and data flows using services like Azure Data Factory.

Now if you’re ready to explore the world of artificial intelligence solutions, then let’s get started!

To get to the next course in this learning path, click on the Learning Path pullout menu on the left side of the page. But please remember to rate this introduction before you go on to the next course. Thanks!


About the Author
Learning Paths

Guy launched his first training website in 1995 and he's been helping people learn IT technologies ever since. He has been a sysadmin, instructor, sales engineer, IT manager, and entrepreneur. In his most recent venture, he founded and led a cloud-based training infrastructure company that provided virtual labs for some of the largest software vendors in the world. Guy’s passion is making complex technology easy to understand. His activities outside of work have included riding an elephant and skydiving (although not at the same time).