Foundations of Search Ranking and Learning to Rank

Search ranking is the core technology powering modern information retrieval systems, digital marketplaces, and search engines. Understanding how algorithms score, sort, and deliver the most relevant results is an essential skill for anyone working in data-driven software development. This text-based course guides you through the fundamental principles of ranking models, from traditional scoring techniques to modern learning-to-rank frameworks. What you'll learn: Understand core terminology and metrics including precision, recall, MAP, and NDCG; Learn pointwise, pairwise, and listwise approaches to learning to rank; Explore feature engineering techniques tailored specifically for search queries and documents; Apply evaluation strategies to benchmark and compare ranking performance; Discover modern retrieval paradigms including dense embeddings and hybrid search workflows. You will start by building a strong conceptual foundation before moving on to practical model formulation and written scenario-based exercises. This course is designed for aspiring data practitioners, developers, and analysts with basic programming curiosity; no prior background in search ranking is required. Begin reading today to master the mechanics behind intelligent search systems.