Gus Schrader

Linear Algebra stuff - matrices, transformations, vector spaces

Set theory, functions and relations, basic propositional logic, epsilon delta proofs, series convergence, modulo arithmetics—overall a hodgepodge of topics from analysis and algebra slow-cooked with logic

I learned how to use matrices to represent linear systems of equations, how to determine linearity, and how to define subspaces and transformations.

Matrices, Vector Spaces, Eigenvalues, Eigenvectors, Linear Transformations, etc.

Constructing proofs and the basics of set theory, analysis and modern algebra.

Image, kernel, span, eigenvalues and eigenvectors - basics of linear algebra

This was a good introduction to a lot of topics in modern algebra, set theory, and analysis. It was also a nice introduction to various proof strategies.

Linear Transformation, eigenspaces, bases, images, kernels

Concrete information about abstract algebra and real analysis.

I absolutely loved this course. We learned about matrices for solving systems of equations, the definition of a linear subspace, the kernel, the image, matrices as linear transformations, generalizations of linear transformations to spaces other than Rn, eigenstuff, diagonalizability, gram-schmidt process for finding an orthonormal basis, singular value decomposition, determinants, etc.