Linear Algebra Foundations for Modern Computing and Data

Linear algebra provides the core mathematical foundation for modern data analysis, machine learning, computer graphics, and scientific computing. This text-based course offers a clear, accessible path to understanding key algebraic concepts and applying them with confidence. What you will learn: Understand fundamental concepts including vectors, vector spaces, and linear combinations. Perform essential matrix operations such as addition, transposition, and matrix multiplication. Solve systems of linear equations using row reduction and Gaussian elimination. Calculate determinants, matrix inverses, and interpret their geometric properties. Explore eigenvalues and eigenvectors and recognize their role in modern data transformations. Connect theoretical matrix algebra to practical computing concepts and dimensionality reduction. You will begin with essential terminology and core definitions before progressing through systematic matrix algebra, computational algorithms, and applied problem-solving. This course is designed for absolute beginners, curious students, and programmers seeking to strengthen their quantitative skills with no prior advanced mathematics required. Begin your reading today to build a solid foundation in linear algebra.