Build a Natural Language Processing Solution with Azure AI Services (AI-3003)

Build a Natural Language Processing Solution with Azure AI Services (AI-3003) is a dynamic one-day course tailored for software developers keen on integrating AI capabilities into their applications utilizing Azure AI Services and Azure AI Language. Throughout the course, participants will utilize either C# or Python programming languages to harness the power of Azure AI Language. Build a Natural Language Processing Solution with Azure AI Services (AI-3003) Benefits In this course, you will learn how to: Designing solutions for processing natural language with Azure AI Language.  Creating solutions for analyzing text using preconfigured features.  Training models for custom language solutions, specifically for question answering and conversational language understanding.  Understanding, synthesizing, and translating speech.  Training Prerequisites Before enrolling in this course, students are expected to have:  Knowledge of Microsoft Azure and the ability to navigate the Azure portal effectively.  Proficiency in either C# or Python programming languages.  Familiarity with JSON and REST programming semantics.  Azure AI Services Natural Language Training Course AI-3003 Outline Module 1: Analyze text with Azure AI Language  Introduction  Provision an Azure AI Language resource  Detect language  Extract key phrases  Analyze sentiment  Extract entities  Extract linked entities  Exercise: Analyze text  Module 2: Build a question answering solution  Introduction  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  Introduction  Understand prebuilt capabilities of 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 a conversational language understanding model  Module 4: Create a custom text classification solution  Introduction  Understand types of classification projects  Understand how to build text classification projects  Exercise: Classify text  Module 5: Create a custom named entity extraction solution  Introduction  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  Introduction  Provision an Azure AI Translator resource  Understand language detection, translation, and transliteration  Specify translation options  Define custom translations  Exercise: Translate text with Azure AI Translator service  Module 7: Create speech-enabled apps with Azure AI services  Introduction  Provision an Azure resource for speech  Use 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 Azure AI Speech service  Introduction  Provision an Azure resource for speech translation  Translate speech to text  Synthesize translations  Exercise: Translate speech