Skills you'll gain

There are 6 modules in this course

We then focus on the geometry of the matrix transformation by studying the eigenvalues and eigenvectors of matrices. These numbers are useful for both pure and applied concepts in mathematics, data science, machine learning, artificial intelligence, and dynamical systems. We will see an application of Markov Chains and the Google PageRank Algorithm at the end of the course.

Subspaces

Determinants

Eigenvectors and Eigenvalues

Diagonalization and Linear Transformations

Final Assessment