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.
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Free Virtual Training Events:
Transforming Business with AI‑Powered Insights (2 May 2025 | 9 AM–5 PM | Virtual)
A live virtual training event, demonstration‑based session that shows how AI can streamline routine tasks, generate content, and deliver intelligent automation without any software setup. Suited to IT professionals, decision‑makers and anyone keen to see enterprise‑grade AI in action.
Enhancing Business Operations with Enhanced Copilot Capabilities (21 May 2025 | 9 AM–5 PM | Virtual)
An interactive virtual training event focused on Microsoft 365 Copilot: learn how chat‑based AI boosts collaboration, how to extend its functionality with custom agents in Copilot Studio, and practical ways to integrate these capabilities into everyday workflows. Ideal for business users seeking measurable efficiency gains.
Skills Covered
- Deploy a language resource, and use prebuilt models
- Create a custom text classification solution
- Create a custom named entity recognition (NER) solution
Who Should Attend
- AI Engineer
- Developer
- Solution Architect
Course Curriculum
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.
Course Modules
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
