Gilbert Strang has taught linear algebra at MIT for more than 50 years and the course he developed has become a model for teaching around the world. His video lectures on MIT OpenCourseWare have been ...

Basic linear algebra methods including basic matrix/vector operations, solution of linear systems of equations, eigenvalues, and singular values. Focus will be on applications of the methods on a ...

This bridge course has a very practical curriculum, which covers the fundamentals of linear algebra as they are used in applied statistics courses. Some of the topics include, but are not limited to, ...

Understanding and implementation of algorithms to calculate matrix decompositions such as eigenvalue/vector, LU, QR, and SVD decompositions. Applications include data-fitting, image analysis, and ...

Linear transformations. Linear operators, change of basis, inner product and the diagonalization problem. Quadratic forms. Convex sets and geometric programming, input/output models for an economy, ...

Vector spaces, linear transformation, matrix representation, inner product spaces, isometries, least squares, generalised inverse, eigen theory, quadratic forms, norms, numerical methods. The fourth ...

Computations that involve matrix algorithms are happening everywhere in the world at every moment in time, whether these be embedded in the training of neural networks in data science, in computer ...

The world falls away, and it’s just me and Panopto, reaching full human potential as one. I live in a double in the Inn on ...

The trouble is that an education concerned foremost with breadth of study is unable to capture what makes each subject ...