Develop natural language processing solutions with Azure AI Services (AI-3003) Training in Greece

 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. 

Who Should Attend?

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.

Students will learn to,

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

Module 1: Analyze text with Azure AI Language

• Detect language from text
• Analyze text sentiment
• Extract key phrases, entities, and linked entities

Module 2: Create question answering solutions with Azure AI Language

• 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.

Module 3: Build a conversational language understanding model

• 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

Module 4: Create a custom text classification solution

• 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

Module 5: Custom named entity recognition

• Understand tagging entities in extraction projects
• Understand how to build entity recognition projects

Module 6: Translate text with Azure AI Translator service

• Provision a 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 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)

Module 8: Translate speech with the Azure AI Speech service

• Provision Azure resources for speech translation.
• Generate text translation from speech.
• Synthesize spoken translations.

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