Foundations of Information Retrieval: Theory and Modern Search Methods

In an era of infinite data, finding the exact information you need quickly and accurately is a fundamental challenge. Understanding how search engines actually process, index, and retrieve text is the first step toward building or optimizing search systems. This text-based course guides you through the core theoretical foundations of information retrieval, helping you transition from basic keyword matching to understanding modern semantic search architectures. What you'll learn: Understand foundational concepts of information retrieval, including inverted indexes and tokenization; Analyze classic retrieval models such as the Boolean model and Vector Space Model; Evaluate search quality using industry-standard metrics like precision, recall, and F-score; Explore modern semantic search concepts, including dense embeddings and vector databases; Apply theoretical search strategies to design efficient queries and structure unstructured data. You will start with key terminology and foundational definitions before progressing to indexing techniques, mathematical retrieval models, and modern vector-based search paradigms. Designed for beginners in computer science, data analysis, or software development, this course requires no prior background in search technologies. Start reading today to master the mechanics behind modern search engines.