hands-on lab

Exploring Azure Question Answering Service

Difficulty: Intermediate
Duration: Up to 1 hour
Students: 249
Rating: 5/5
Get guided in a real environmentPractice with a step-by-step scenario in a real, provisioned environment.
Learn and validateUse validations to check your solutions every step of the way.
See resultsTrack your knowledge and monitor your progress.

Description

Azure AI Services (formerly known as Azure Cognitive Services) is a cloud-based service that provides a set of APIs for building intelligent applications. The service is composed of various APIs that are categorized into five main categories: Vision, Speech, Language, Web Search, and Decision. It allows developers to easily add intelligent features, such as emotion and video detection, facial, speech and vision recognition, and speech and language understanding, into their applications and build smart applications.

Azure Question Answering service (formerly known as QnA Maker) is one of the capabilities of Azure AI Services. It allows developers to add question-and-answer capabilities to their applications. It is a cloud-based service that uses machine learning to answer questions based on the best possible answer. It can be used to build applications that can answer questions based on a knowledge base or a set of documents.

In this hands-on lab, you will learn how to create a question-and-answer application using Azure Question Answering service. You will create a knowledge base using a set of documents and then use the knowledge base to answer questions.

Learning objectives

Upon completion of this intermediate-level lab, you will be able to:

  • Understand the basics of Azure Question Answering service
  • Create a knowledge base using external URLs
  • Deploy the question-answering application bot
  • Test the question-answering application bot

Intended audience

  • Candidates for AI-102 (Designing and Implementing a Microsoft Azure AI Solution certification)
  • Cloud Architects
  • Data Engineers
  • Machine Learning Engineers
  • Software Engineers

Prerequisites

Familiarity with the following will be beneficial but is not required:

  • Azure AI Services

The following content can be used to fulfill the prerequisites:

Environment before

Environment after

Covered topics

Lab steps

Logging in to the Microsoft Azure Portal
Creating and Deploying QnA Project Using Azure AI Language Studio
Testing QnA Bot Using Bot Web Chat