Since Spring 2015, I’ve worked as a course assistant (CA) for the ACE program. Most of my time as a CA for this program has been spent working with Prof. Hung Le in CME 100 and 102, and in the process I have developed a large number of materials for these courses.
As a side project, I set out to make section notes for my CME 102 students. The general idea was to make lecture notes that were clean, easily-digestible, and high-quality, since these were something I found lacking in a lot of online resources for the material in math and engineering courses. A big inspiration for these notes was Andrej Karpathy’s notes for CS 231N on deep learning, which clearly and concisely teaches you the bare essentials for deep learning. In general, the machine learning/deep learning/AI community has a ton of great blog posts and other resources for learning about that field. I’m hoping these can provide a similar resource for introductory differential equations.
In the pages linked below, I’ve compiled all of my course notes and ACE section materials. I hope that this provides a centralized resource for students in Stanford’s undergraduate CME series (and perhaps even for students from other schools in similar classes). Note: these notes are not meant to replace the course readers for these classes, and certainly are not a substitute for class attendance. They are just a compilation of notes and practice problems from an experienced TA.