AI-3003 Develop natural language solutions in Azure
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Upcoming Class Schedule
$695.00
Sep 29 - Sep 29, 2026
9:00 AM - 5:00 PM America/New_York- VILT
- Jan 18 - Jan 18, 2027
- 9:00 AM - 5:00 PM America/New_York
- VILT
Prerequisites for AI-3003 Develop natural language solutions in Azure Course
AI-3003 Develop natural language solutions in Azure Course Outline
- Azure Language in Microsoft Foundry Tools
- Detect language
- Extract key phrases
- Analyze sentiment
- Extract entities
- Extract linked entities
- Module assessment
- Understand the Azure Language MCP server
- Connect and use the Language MCP server with an agent
- Choose a speech-capable model
- Transcribe speech
- Synthesize speech
- Module assessment
- Azure Speech in Foundry Tools
- Use the Speech to Text API
- Use the Text to Speech API
- Configure audio format and voices
- Use Speech Synthesis Markup Language
- Module assessment
- Understand the Azure Speech MCP server
- Connect and use the Speech MCP server with an agent
- Explore the Azure Voice Live API
- Explore the AI Voice Live client library for Python
- Create a Voice Live agent
- Module assessment
- Translation in Microsoft Foundry
- Translate text
- Translate speech
- Module assessment
Resources
FAQs on AI-3003 Develop natural language solutions in Azure
You’ll learn to build natural language processing solutions on Azure, including text analysis (language detection, sentiment analysis, key phrase and entity extraction), speech-to-text and text-to-speech capabilities, and how to integrate these features into AI agents using Azure Language and Speech MCP servers within Microsoft Foundry Tools.
You should be familiar with Azure and the Azure portal, and have prior programming experience with either C# or Python.
This course is designed for developers and AI engineers who want to build intelligent applications that process natural language and speech, leveraging Azure Cognitive Services and Foundry Tools within their existing Azure-based development workflows.
Yes, the course covers both. It includes modules on analyzing text (sentiment, entities, key phrases) with Azure Language, as well as building speech-enabled applications using Azure Speech, including transcription, synthesis, and Speech Synthesis Markup Language (SSML).
MCP (Model Context Protocol) servers allow AI agents to connect to and utilize Azure Language and Speech services directly. The course teaches you how to integrate these MCP servers with agents to build more capable, context-aware natural language and speech applications.