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

Important - This course has MFA Requirements. Please read this link and download the MFA app, prior to attending.

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

Microsoft Azure learning paths

= Required
= Certification
Data Scientist
Data Engineer
Developer .NET Experience
Architect Enterprise Architecture Experience
Administrator DevOps Windows Administration Experience
Administrator Security Windows Administration Experience
Administrator Architect Windows Administration Experience
AI Engineer
Data Engineer Average salary: £70,000
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