Overview

Natural language processing (NLP) solutions use language models to interpret the semantic meaning of written or spoken language. You can use the Language Understanding service to build language models for your applications.
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Prerequisites

Before starting this Workshop, you should already have:
  • Familiarity with Azure and the Azure portal.
  • Experience programming with C# or Python. If you have no previous programming experience, we recommend you complete the Take your first steps with C# or Take your first steps with Python learning path before starting this one.
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Outline

Module 1: Analyze text with Azure AI Language
The Azure AI Language service enables you to create intelligent apps and services that extract semantic information from text.
  • Introduction
  • Provision an Azure AI Language resource
  • Detect language
  • Extract key phrases
  • Analyze sentiment
  • Extract entities
  • Extract linked entities
  • Exercise - Analyze text
  • Knowledge check
  • Summary
Module 2: Build a question answering solution
The question answering capability of the Azure AI Language service makes it easy to build applications in which users ask questions using natural language and receive appropriate answers.
  • Introduction
  • Understand question answering
  • Compare question answering to Azure AI Language understanding
  • Create a knowledge base
  • Implement multi-turn conversation
  • Test and publish a knowledge base
  • Use a knowledge base
  • Improve question answering performance
  • Exercise - Create a question answering solution
  • Knowledge check
  • Summary
Module 3: Build a conversational language understanding model
The Azure AI Language conversational language understanding service (CLU) enables you to train a model that apps can use to extract meaning from natural language.
  • Introduction
  • Understand prebuilt capabilities of the Azure AI Language service
  • Understand resources for building a conversational language understanding model
  • Define intents, utterances, and entities
  • Use patterns to differentiate similar utterances
  • Use pre-built entity components
  • Train, test, publish, and review a conversational language understanding model
  • Exercise - Build an Azure AI services conversational language understanding model
  • Knowledge check
  • Summary
Module 4: Create a custom text classification solution
The Azure AI Language service enables processing of natural language to use in your own app. Learn how to build a custom text classification project.
  • Introduction
  • Understand types of classification projects
  • Understand how to build text classification projects
  • Exercise - Classify text
  • Knowledge check
  • Summary
Module 5: Create a custom named entity extraction solution
Build a custom entity recognition solution to extract entities from unstructured documents
  • Introduction
  • Understand custom named entity recognition
  • Label your data
  • Train and evaluate your model
  • Exercise - Extract custom entities
  • Knowledge check
  • Summary
Module 6: Translate text with Azure AI Translator service
The Translator service enables you to create intelligent apps and services that can translate text between languages.
  • Introduction
  • Provision an Azure AI Translator resource
  • Understand language detection, translation, and transliteration
  • Specify translation options
  • Define custom translations
  • Exercise - Translate text with the Azure AI Translator service
  • Knowledge check
  • Summary
Module 7: Create speech-enabled apps with Azure AI services
The Azure AI Speech service enables you to build speech-enabled applications. This module focuses on using the speech-to-text and text to speech APIs, which enable you to create apps that are capable of speech recognition and speech synthesis.
  • Introduction
  • Provision an Azure resource for speech
  • Use the Azure AI Speech to Text API
  • Use the text to speech API
  • Configure audio format and voices
  • Use Speech Synthesis Markup Language
  • Exercise - Create a speech-enabled app
  • Knowledge check
  • Summary
Module 8: Translate speech with the Azure AI Speech service
Translation of speech builds on speech recognition by recognizing and transcribing spoken input in a specified language, and returning translations of the transcription in one or more other languages.
  • Introduction
  • Provision an Azure resource for speech translation
  • Translate speech to text
  • Synthesize translations
  • Exercise - Translate speech
  • Knowledge check
  • Summary
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Why choose QA

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QA online courses, also commonly known as distance learning courses or elearning courses, take the form of interactive software designed for individual learning, but you will also have access to full support from our subject-matter experts for the duration of your course. When you book a QA online learning course you will receive immediate access to it through our e-learning platform and you can start to learn straight away, from any compatible device. Access to the online learning platform is valid for one year from the booking date.

All courses are built around case studies and presented in an engaging format, which includes storytelling elements, video, audio and humour. Every case study is supported by sample documents and a collection of Knowledge Nuggets that provide more in-depth detail on the wider processes.

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Certificates of Achievement are issued at the end the course, either as a hard copy or via email. Read more here.

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