We provide virtual course about develop natural language solutions in Azure (AI-3003) (M-AI3003). Natural language processing (NLP) solutions use language models to interpret the semantic meaning of written or spoken language.
Course overview:
You can use the Language Understanding service to build language models for your applications
In this course you’ll learn:
• 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
• Develop an audio-enabled generative AI application
Course content:
Module 1 - Analyze text with Azure AI Language:
• Provision an Azure AI Language resource
• Detect language
• Extract key phrases
• Analyze sentiment
• Extract entities
• Extract linked entities
Module 2 - Create question answering solutions with Azure AI Language:
• Understand question answering
• Compare question answering to Azure AI Language understanding
• Create a knowledge base
• Implement multi-turn conversation
• Test and publish a knowledge base
• Use a knowledge base
• Improve question answering performance
• Exercise - Create a question answering solution
Module 3 - Build a conversational language understanding model:
• Understand prebuilt capabilities of the Azure AI Language service
• Understand resources for building a conversational language understanding model
• Define intents, utterances, and entities
• Use patterns to differentiate similar utterances
• Use pre-built entity components
• Train, test, publish, and review a conversational language understanding model
• Exercise - Build an Azure AI services conversational language understanding model
Module 4 - Create a custom text classification solution:
• Understand types of classification projects
• Understand how to build text classification projects
• Exercise - Classify text
Module 5 - Custom named entity recognition:
• Understand custom named entity recognition
• Label your data
• Train and evaluate your model
• Exercise - Extract custom entities
Module 6 - Translate text with Azure AI Translator service:
• Provision an Azure AI Translator resource
• Understand language detection, translation, and transliteration
• Specify translation options
• Define custom translations
• Exercise - Translate text with the Azure AI Translator service
Module 7 - Create speech-enabled apps with Azure AI services:
• Provision an Azure resource for speech
• Use the Azure AI Speech to Text API
• Use the text to speech API
• Configure audio format and voices
• Use Speech Synthesis Markup Language
• Exercise - Create a speech-enabled app
Module 8 - Translate speech with the Azure AI Speech service:
• Provision an Azure resource for speech translation
• Translate speech to text
• Synthesize translations
• Exercise - Translate speech
Module 9 - Develop an audio-enabled generative AI application:
• Deploy a multimodal model
• Develop an audio-based chat app
• Exercise - Develop an audio-enabled chat app
Target audience:
Anyone who wants virtual course about develop natural language solutions in Azure (AI-3003)
Prerequisites:
Before starting this course, 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.