Overview
Develop natural language processing solutions with Azure AI Services
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.
As of 13th June, the AI-102 Develop AI Solutions in Azure course has been updated and restructured by combining together these five 1-day AI courses into a single, comprehensive learning experience:
- AI-3016: Develop generative AI apps in Azure
- AI-3026: Develop AI Agents on Azure
- AI-3002: Develop AI information extraction solutions in Azure
- AI-3003: Build a natural language processing solution with Azure AI Services
- AI-3004: Build an Azure AI Vision solution with Azure AI services
This update provides learners with a more cohesive and in-depth journey through key AI concepts and applications.
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Why Choose KORNERSTONE
- Accredited, practitioner-led, expert certificate trainers to provide high quality training
- Official training material included
- Practical, scenario-based learning – focus on application, not just theory
- Excellent Passing Rate
Skills Covered
- Deploy a language resource, and use prebuilt models
- Create a custom text classification solution
- Create a custom named entity recognition (NER) solution
Prerequisites
Before starting this learning path, 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.
Target Audience
- AI Engineer
- Developer
- Solution Architect
Course Curriculum
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.
Learning objectives
In this module, you’ll learn how to use the Azure AI Language service to:
- Detect language from text
- Analyze text sentiment
- Extract key phrases, entities, and linked entities
Prerequisites
Before starting this module, you’ll need
- Familiarity with Microsoft Azure and the Azure portal.
- Experience programming with C# or Python.
Module 2: Create question answering solutions with Azure AI Language
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.
Learning objectives
After completing this module, you will be able to:
- Understand question answering and how it compares to language understanding.
- Create, test, publish, and consume a knowledge base.
- Implement multi-turn conversation and active learning.
- Create a question answering bot to interact with using natural language.
Prerequisites
Before starting this module, 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 first.
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.
Learning objectives
After completing this module, you’ll be able to:
- Provision Azure resources for Azure AI Language resource
- Define intents, utterances, and entities
- Use patterns to differentiate similar utterances
- Use pre-built entity components
- Train, test, publish, and review an Azure AI Language model
Prerequisites
Before starting this module, 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 first.
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.
Learning objectives
After completing this module, you’ll be able to:
- Understand types of classification projects
- Build a custom text classification project
- Tag data, train, and deploy a model
- Submit classification tasks from your own app
Prerequisites
Before starting this module, you should be familiar with:
- The Azure portal
- Familiarity with Azure AI Services
- General programming techniques
Module 5: Create a custom named entity extraction solution
Build a custom entity recognition solution to extract entities from unstructured documents
Learning objectives
After completing this module, you’ll be able to:
- Understand custom named entities and how they’re labeled.
- Build a Language service project.
- Label data, train, and deploy an entity extraction model.
- Submit extraction tasks from your own app.
Prerequisites
Before starting this module, you should be familiar with:
- The Azure portal
- General functionality of Azure AI Services
- General programming technique
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.
Learning objectives
After completing this module, you’ll be able to:
- Provision a Translator resource
- Understand language detection, translation, and transliteration
- Specify translation options
- Define custom translations
Prerequisites
Before starting this module, you need
- Familiarity with Microsoft Azure and the Azure portal.
- Experience programming with C# or Python.
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.
Learning objectives
In this module, you’ll learn how to:
- Provision an Azure resource for the Azure AI Speech service
- Use the Azure AI Speech to text API to implement speech recognition
- Use the Text to speech API to implement speech synthesis
- Configure audio format and voices
- Use Speech Synthesis Markup Language (SSML)
Prerequisites
Before starting this module, you should:
- Be familiar with Azure services and the Azure portal
- Have experience programming with C# or Python
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.
Learning objectives
In this module, you will learn how to:
- Provision Azure resources for speech translation.
- Generate text translation from speech.
- Synthesize spoken translations.
Prerequisites
Before starting this module, you should:
- Be familiar with Azure services and the Azure portal.
- Have experience programming with C# or Python.
- Have experience of using the Azure AI Speech service to transcribe speech to text.
Dates & Locations
October 6, 2026
October 6, 2026
Exam & Certification
To earn this Microsoft Applied Skills credential, learners demonstrate the ability to create a natural language processing (NLP) solution by using Azure AI Language.
Candidates for this credential should have a solid understanding of creating and using various Azure NLP models through both Language Studio and in code, including custom models. They should also have experience programming in either Python or C#, be familiar with the Azure portal, and be comfortable provisioning Azure AI resources.
Tasks performed
- Deploy a language resource, and use prebuilt models
- Create a custom text classification solution
- Create a custom named entity recognition (NER) solution
