Implementing Knowledge Mining with Azure AI Search

Organizations are flooded with unstructured data, such as PDFs, images, and documents, containing valuable insights locked away in unsearchable formats. Knowing how to ingest, enrich, and query this data is a crucial skill for modern data and cloud professionals. This written course guides you through the process of building intelligent search engines using Azure AI Search, transitioning you from understanding core search concepts to configuring complex ingestion pipelines that extract, enrich, and index your data. What you'll learn: - Understand foundational knowledge mining concepts, search indexing terminology, and service architecture. - Configure data ingestion pipelines to import unstructured data from cloud storage sources. - Create cognitive skillsets utilizing natural language processing to enrich your search index with AI-generated metadata. - Apply modern vector search and semantic ranking techniques to deliver highly relevant, context-aware search results. - Design index schemas, custom analyzers, and scoring profiles to fine-tune search relevance. - Integrate enriched search data with retrieval-augmented generation patterns for downstream AI applications. You will begin by learning core definitions and the anatomy of a search service before moving step-by-step through index creation, cognitive enrichment, and advanced query techniques. The material features clear written explanations, conceptual breakdowns, and practical configuration examples. Designed for beginners, developers, and data professionals new to cloud-hosted search technologies, this course requires no prior experience with Azure AI Search. Start reading today to unlock the hidden value in your organization's unstructured data.