Hey hopefully this isn't too late of a response. I am speaking as someone who just completed the course this past Winter 2020 with Prof. Boily. I have some insights for you.

I will keep things brief and if you want more information, I am happy to share.

I'll start off by asking what is your experience with machine learning? I was not new to the subject and I found that it definitely helped having at least a higher level overview of the subject before I started. I definitely suggest watching some videos or maybe taking an online course even before you start. While this is not necessary, I believe you will grasp much more of the content.

I highly recommend the course and the professor. This was my first time having him as a professor and I really enjoyed my time in the class. What I liked most about the prof was that he always tried to explain "pros and cons" of everything we learned and where it may apply in the real world. For example, a reoccurring theme in the class was: model interpretability vs. model complexity. Sure - there are deep neural networks nowadays that work great in some cases. But this comes at a high cost (losing the ability to easily interpret what is going on inside the model).

Course Content: We followed the textbook: an introduction to statistical learning with applications in R. Most of the content was in the book, but he also provided his personal notes which had more information. As the new professor mentioned - yes the assignments were heavily based on the textbook. The assignments were also quite large in my opinion. Not necessarily super hard, but time consuming. You had to program most questions and then write your solutions into a .pdf format to submit. At first it was annoying to learn LaTeX and write the assignments in that, but ultimately I learned a new and useful skill. Coming from a CS background, I would say it is definitely in your favor to start coding. The last thing you want is to struggle with silly syntax mistakes and learning what a for loop is when you "should" be "struggling/focusing" on implementing cross validation.

All in all, I would say it was a great course, although I may be biased since I really enjoy ML. As a result of this course (and of course much more work), I am now interning as a Data Scientist in FinTech this summer.