Practical Linear Algebra for Programmers

Many modern programming fields—from game development and computer graphics to machine learning and data science—rely heavily on linear algebra. Understanding the math behind these technologies is key to writing efficient code and solving complex computational problems. This text-based course bridges the gap between abstract mathematics and practical programming, helping you build a solid intuitive understanding of core algebraic concepts and see exactly how they translate into software applications. What you'll learn: - Understand foundational concepts of vector spaces, dimensions, and coordinate systems. - Perform matrix operations, including multiplication, transposition, and inversion, with a focus on computational efficiency. - Apply linear transformations, rotations, and scaling vectors used in computer graphics and game physics. - Explore eigenvectors and eigenvalues and their real-world use in dimensionality reduction and data analysis. - Analyze how modern AI applications use vector embeddings to represent complex text and image data. - Practice solving algebraic equations programmatically through written step-by-step exercises. The course starts with fundamental definitions of vectors and matrices, gradually moving from theoretical math to practical application scenarios. You will read clear explanations, study illustrative code snippets, and reinforce your knowledge through targeted written exercises. Designed for beginner developers, self-taught programmers, and computer science students looking to strengthen their mathematical foundations, this course requires no advanced math background as we start from the absolute basics. Start reading today to unlock the mathematical principles behind modern software development.