Linear Algebra Foundations: Vectors, Matrices, and Data Science

Linear algebra forms the essential mathematical bedrock of modern computing, data science, and artificial intelligence. Understanding how vectors and matrices interact provides crucial insight into how algorithms represent, manipulate, and analyze complex information under the hood. This beginner-friendly text course guides you through foundational concepts of linear algebra, translating mathematical theory into practical visual thinking for data analysis. You will start by learning fundamental terminology, notation, and basic vector properties before building up to multi-dimensional matrix operations. What you will learn: Learn the core terminology and properties defining vectors and matrices in computational contexts; Master vector-matrix multiplication, dot products, and basic matrix operations; Understand how dataset features are represented as multi-dimensional vectors and embeddings; Practice visualizing linear transformations and their applications in data processing; Discover how linear algebra powers modern data analysis techniques and AI algorithms. You will progress smoothly from basic definitions through structured written explanations and step-by-step calculation examples. This course is designed for absolute beginners, aspiring data analysts, and tech enthusiasts seeking a solid theoretical foundation without complex prerequisites. Start reading today to unlock the mathematical principles behind modern data analysis.