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

This is a subject I struggled with the first time I took it. Ironically, this was the engineering version of it. It wasn't until I took the rigorous, axiomatic version that everything clicked.

*Note: This course discription is only applicable to the Computer Science Post-Baccalaureate program. Additionally, students must always refer to course syllabus for the most up to date information.

Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and ...

This asynchronous online bridge course is specifically designed to help students satisfy the linear algebra admissions requirements for Michigan Tech's Online MS in Applied Statistics, an innovative ...

The class of second-order linear dynamical systems is considered. A method and algorithm are presented to transform any system with n degrees of freedom into n independent second-order equations. The ...

These pages provide a showcase of how to use Python to do computations from linear algebra. We will demonstrate both the NumPy (SciPy) and SymPy packages. This is meant to be a companion guide to a ...