Learn the concepts and methods of linear algebra, and how to use them to think about computational problems arising in computer science. Coursework includes building on the concepts to write small programs and run them on real data.
You should be an experienced programmer. We use a subset of Python in this course, and we start by covering the relevant features and syntax, so many students find they can get by without prior knowledge of Python.
You are not expected to have any background in linear algebra. However, you should be prepared to read and understand some mathematical proofs. At Brown University, a similar course is taken mostly by sophomore computer science majors who have taken at least two semesters of programming and one semester addressing proof techniques.
Coding the Matrix is an optional companion textbook. It covers the material addressed by this course, plus additional examples and more advanced topics not covered by the course (wavelets, discrete Fourier transforms, singular value decomposition, eigenvalues, and linear programming). The textbook is not at all necessary for taking the course; all necessary material is covered in lecture.