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, ...

An introduction to proofs and the axiomatic methods through a study of the vector space axioms. Linear analytic geometry. Linear dependence and independence, subspaces, basis. Inner products. Matrix ...

Introduces the fundamentals of linear algebra in the context of computer science applications. Includes vector spaces, matrices, linear systems, and eigenvalues. Includes the basics of floating point ...

These collections are called groups. The simpler objects are arrays of numbers called matrices, the core element of linear algebra. While groups are abstract and often difficult to get a handle on, ...

It consists of the linear algebra part of MA212, covering the following topics: Vector spaces and dimension. Linear transformations, kernel and image. Real inner products. Orthogonal matrices, and the ...

They go further: “Numerical linear algebra is really functional analysis ... Topics include the basics (matrix operations, norms, and the SVD), QR factorization and least squares, conditioning and ...

Again, the professor in that class took some interest in me, offered me a research project, and that’s how I started working on things related to matrices and linear algebra. From there ...

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