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AI-900 Exam Preparation: Introduction

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Introduction

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AI-900 Exam Preparation: Introduction
Overview
DifficultyBeginner
Duration2m
Students53
Ratings
5/5
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Description

This course introduces the AI-900 Exam Preparation: Microsoft Azure AI Fundamentals learning path, which covers the following five subject areas in preparation for Microsoft's AI-900 exam:

  • AI workloads
  • Fundamental principles of machine learning on Azure
  • Features of computer vision workloads on Azure
  • Features of natural language processing workloads on Azure
  • Features of conversational AI workloads on Azure

Transcript

Hello and welcome to Microsoft Azure AI Fundamentals. The focus of this learning path is to prepare you for Microsoft’s AI-900 exam.

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

The AI-900 exam tests your knowledge of five subject areas: AI workloads, fundamental principles of machine learning on Azure, features of computer vision workloads on Azure, features of natural language processing workloads on Azure, and features of conversational AI workloads on Azure.

We’ll start this learning path with an introduction to Azure Machine Learning designer, which is a drag-and-drop interface for training and deploying machine learning models without writing any code. You’ll learn some of the fundamentals of machine learning, such as how to prepare data and how to evaluate a trained model. You’ll also learn about the most common types of machine learning, including classification, regression, and clustering.

Next, we’ll focus on the Cognitive Services suite, which 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.

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.

After that, we’ll show you how to build a chatbot using the Azure Bot Service. Probably the most common use for chatbots is customer support. You’ll also learn how to use QnA Maker, which lets you take an existing frequently asked questions page and feed it into your chatbot so it’ll know how to answer common questions.

Finally, we’ve included a Recommended Reading list. It gives you links to articles that explain topics that weren’t covered in the rest of this learning path.

Now if you’re ready to learn the fundamentals of artificial intelligence solutions on Azure, 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
Students60295
Courses62
Learning paths65

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).