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

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

This learning path helps prepare you for Exam AI-102: Designing and Implementing a Microsoft Azure AI Solution.

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

  • Analyze text with Azure AI Language
  • Build a question answering solution
  • Build a conversational language understanding model
  • Create a custom text classification solution
  • Create a custom named entity extraction solution
  • Translate text with Azure AI Translator service
  • Create speech-enabled apps with Azure AI services
  • Translate speech with the Azure AI Speech service

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Key Point of Training Programs

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

    - Analyze text with Azure AI Language
    - Build a question answering solution
    - Build a conversational language understanding model
    - Create a custom text classification solution
    - Create a custom named entity extraction solution
    - Translate text with Azure AI Translator service
    - Create speech-enabled apps with Azure AI services
    - Translate speech with the Azure AI Speech service

  • Build a natural language processing solution with Azure AI Services AI-3003 Delivery Format

    In-Person

    Online

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

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