This class is a referesher that should also encourage you to look by yourself for material that we will not have the time to cover.
What is taught in this class is classical and you can find many good material on internet to complement the lecture. Here are some references:
(Excellent) videos of Gilbert Strang lectures on Linear Algebra (MIT)
First part of the lecture “Introduction to Probability, Statistics, and Machine Learning” by Samuel S. Watson from Brown University
Notes from Zico Kolter (updated Chuong Do), Stanford university, “Linear Algebra Review and Reference”