AI-3003: Build a natural language processing solution with Azure AI Services

Course AI-3003: Build a natural language processing solution with Azure AI Services

To earn this Microsoft Applied Skills credential, students demonstrate the ability to create a natural language processing (NLP) solution using Azure AI Language .

Candidates for this credential should have a solid understanding of creating and using various Azure NLP models through Language Studio and in code, including custom models. They should also have programming experience in Python or C# , be familiar with the Azure portal , and be comfortable provisioning Azure AI resources.

Intermediate - AI Engineer - Developer - Azure AI services

AI-3003 Training Objectives

• Implement a language resource and use pre-built models
• Create a custom text classification solution
• Create a custom named entity recognition (NER) solution

AI-3003 Course Content

Module 1 Text Analysis with Azure AI Language

• Provision an Azure AI Language resource
• Detect language
• Keyphrase Extraction
• Opinion analysis
• Extract entities
• Extraction of linked entities
• Exercise: Text Analysis

Module 2 Creating a Question Answering Solution

• Description of the answer to questions
• Comparing Question Responses with Azure AI Language Understanding
• Creating a knowledge base
• Implement a multi-turn conversation
• Testing and publishing a knowledge base
• Using a knowledge base
• Improved question answering performance
• Exercise: Creating a Question-Answering Solution

Module 3 Creating a Conversational Language Recognition Model

• Recognizing the built-in capabilities of the Azure AI Language service
• Description of resources for creating a conversational language recognition model
• Definition of intentions, expressions and entities
• Using patterns to differentiate similar expressions
• Using pre-built entity components
• Training, testing, publishing, and reviewing a conversational language recognition model
• Exercise: Creating an Azure AI Services Conversational Language Recognition Model

Module 4 Creating a Custom Text Classification Project

• Introduction
• Description of classification project types
• Description of how to compile text classification projects
• Exercise: Text Classification

Module 5: Creating a Custom Named Entity Extraction Solution

• Description of custom named entity recognition
• Data labeling
• Model training and evaluation
• Exercise: Extracting Custom Entities

Module 6: Translating Text with the Azure AI Translator Service

• Provisioning an Azure AI Translator resource
• Understanding language detection, translation, and transliteration
• Specify translation options
• Define custom translations
• Exercise: Translating Text with the Azure AI Translator Service

Module 7: Building Voice-Enabled Applications with Azure AI Services

• Provisioning an Azure resource for voice
• Using the Azure AI Speech-to-Text API
• Using the Text to Speech API
• Setting the audio format and voices
• Using Speech Synthesis Markup Language
• Exercise: Creating a Voice-Enabled Application

Module 8: Speech Translation with Azure AI Speech Service

• Provisioning an Azure resource for speech translation
• Voice to text translation
• Synthesis of translations
• Exercise: Translate voice

Prerequisites

Before starting this learning path, you should have the following:

• Familiarity with Azure and the Azure Portal
• Experience programming with C# in Python. If you have no previous programming experience, it's recommended to complete the Getting Started with C# or Getting Started with Python learning path before starting this one.

Language

• Course: English / Spanish
• Labs: English / Spanish

Microsoft Applied Skills

This course is part of the Microsoft Applied Skills Credentials.

To earn this Microsoft Applied Skills credential, students demonstrate the ability to create a natural language processing (NLP) solution using Azure AI Language.

Applied Skills: Explore all credentials in one guide