<p>Imperial College London's Mathematics for Machine Learning: Linear Algebra is a Coursera MOOC that builds the linear-algebra foundations used in modern machine learning and data science. It is the first course in the Mathematics for Machine Learning Specialisation and is taught by David Dye, Samuel J. Cooper and A. Freddie Page.</p><ul><li>Eligibility: open to anyone; suits JC2 / post-A-Level students with a solid algebra background</li><li>Topics: vectors, dot products and projections, basis and linear independence, matrix transformations, solving linear systems, eigenvalues and eigenvectors</li><li>Applications include PCA-style dimensionality reduction, image transformations and Google's PageRank</li><li>Format: five modules with quizzes, programming projects and Jupyter/Python labs</li><li>Cost: free to audit; a verified certificate is available for purchase, with financial aid options</li></ul><p>Learners enrol directly on the Coursera course page and progress at their own pace.</p>