Module overview
A module focussed on properly understanding linear-algebra/matrices, which gives a lot of insight into how computation works, gives great perspective into many problems in mechanics, gives the language to describe machine learning, and has many other benefits. Matrices are used everywhere. The course will cover matrix inversion, algorithms for Ax=b, vector spaces, projection, properties of determinants, eigenvalues and eigenvectors, symmetric matrices, singular value decomposition. As we go through these general ideas, we will consider specific applications such as finite difference method for partial differential equations, linear regression, principal component analysis, trusses, numerical differentiation and integration, systems of ordinary differential equations, linear programming, neural networks, and others. Fundamentally, this is a mathematics course, but it is strongly focussed on intuitive understanding and applying the mathematics to different engineering problems.