NLP and Generative AI on Azure

This unit explores natural language and speech processing fundamentals, generative AI principles, and the Microsoft Azure services that enable them. Students will learn preprocessing, modeling, translation, evaluation, ethics, and how to integrate Azure AI Language, Speech, Translator, Cognitive Search, and Azure OpenAI into application workflows while preparing for certification objectives.

Learning Objectives

• Analyze core NLP and speech processing techniques (text preprocessing, representation, language modeling, classification, information extraction, generation, and machine translation) and map these techniques to appropriate Azure service capabilities.
• Apply Azure AI Language, Speech, Translator, and Cognitive Search services to design, build, and test text- and speech-based features (e.g., classification, sentiment analysis, speech-to-text, text-to-speech, translation, and semantic search) and integrate them into simple applications.
• Demonstrate understanding of generative model families, training and inference mechanics and implement generation tasks (text and image) using Azure OpenAI and related Azure services, including service configuration and API integration.
• Evaluate model performance, alignment, and ethical considerations (accuracy metrics, bias, privacy, safety) using standard evaluation methods and propose mitigation strategies; complete targeted exam essentials and review activities to prepare for the Microsoft Azure AI Fundamentals certification.