Linear Algebra

Visual intuition for vectors, matrices, determinants, eigenvalues, and abstract spaces. Short chapters that make the geometry of linear algebra click before you dive into the algebra-heavy stuff.

The classic full lecture series from MIT. Strang explains row reduction, subspaces, orthogonality, eigenvalues, and SVD with unmatched clarity. Pair with his book if you want exercises.

Chapter-by-chapter walkthrough of Axler’s proof-centric approach: abstract vector spaces first, determinants later. Great if you want rigorous foundations beyond “matrix recipes.”

Tons of worked problems on matrices, systems, determinants, and eigenvalues. Useful when you already know the rules and need repetition before an exam.

Full OCW package: Strang’s lectures, problem sets, exams with solutions, and lecture notes. The standard free reference for a first serious course in linear algebra.

Structured units from vectors through eigen-everything, with interactive exercises. Ideal for filling gaps or reviewing before harder courses.

Clear written notes and examples on systems, matrices, vector spaces, eigenvalues, and numerical topics. Handy as a reference next to lectures or a textbook.