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

Dynamics Edge courses and labs are enhanced Instructor-Led Training (ILT) materials, purpose-built for live, guided instruction, structured learning and practical, work-ready skills development.

Unlike Microsoft Learn paths—which are designed for self-paced study—our ILT content follows a carefully crafted curriculum tailored for real-time engagement, interactive Q&A, The structure and flow of our materials are intentionally different to support deeper learning and immediate application.

Course Overview

This course, AI-3003, provides an in-depth exploration of natural language processing (NLP) techniques and how to implement them using Azure AI Services. Participants will learn foundational NLP concepts, advanced techniques, and practical skills for building and deploying NLP solutions in various applications.

Course Objectives

By the end of this course, participants will be able to:

1. Understand the fundamental concepts of natural language processing.
2. Use Azure AI Services to develop NLP models.
3. Apply NLP techniques in real-world applications.
4. Deploy and monitor NLP solutions on Azure.

Course Outline

Module 1:  Analyze text with Azure AI Language

• Provision an Azure AI Language resource
• Detect language
• Extract key phrases
• Analyze sentiment
• Extract entities
• Extract linked entities

Module 2:  Build a question answering solution

• 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

Module 3:  Build a conversational language understanding model

• 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

Module 4:  Create a custom text classification solution

• Understand types of classification projects
• Understand how to build text classification projects

Module 5:  Create a custom named entity extraction solution

• Understand custom named entity recognition
• Label your data
• Train and evaluate your model

Module 6:  Translate text with Azure AI Translator service

• Provision an Azure AI Translator resource
• Understand language detection, translation, and transliteration
• Specify translation options
• Define custom translations

Module 7:  Create speech-enabled apps with Azure AI services

• 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

Module 8:  Translate speech with the Azure AI Speech service

• Provision an Azure resource for speech translation
• Translate speech to text
• Synthesize translations