This class was an incredibly interesting elective, and it was not difficult AT ALL. I have no coding experience and was able to teach myself basic Python and walk away with an A+. Despite that I think it should probably be required to have taken linear algebra and/or basic coding before this (without the former I would have dropped). In lecture, Dr. Bouchard talks about various algorithms and their applications for machine learning along with specific functions that are utilized by these algorithms. He also covers derivations for some of the functions, but all of what is taught in lecture is done for your knowledge only. There are no tests in this class because he stated his belief that coding exams are a waste of time because anybody in the real world needs to look at documentation and take their time.

Your grade in this class is determined purely 3 homework assignments, a final project, and a tiny bit of attendance. The latter is checked at random maybe 5 times throughout the quarter, usually on days where he sees attendance is low and decides to pull out a piece of paper for you to write your name on. The homework assignments come out every few weeks and you're given like 2 weeks to do them; each one consists of 3-5 questions centered around an algorithm and your ability to apply it in Python. Some sub questions are just about what your code does and interpretations of the code. They're graded very leniently (probably just on whether or not it functions properly) since I wrote incredibly messy, inefficient code and got >93 on all assignments. If you filled out a course evaluation at the end of the quarter, Dr. Bouchard also said that he'd drop one. The final project was also incredibly simple, with several topics to choose from applying machine learning to the real world, with the most important part being that Dr. Bouchard WROTE CODE FOR ALL OPTIONS and then gave it to the class to modify slightly for their project. The project was therefore pretty much just interpreting what his code was doing.

As for Dr. Bouchard himself, he's a very nice, responsive person who is more than willing to answer questions and stay after class to help with understanding machine learning applications or troubleshooting the homework. It's very clear to me that he's ridiculously smart but I don't think it really gets in the way of him being an effective communicator. He made the class pretty interesting and fun.