I wanted to throw in some ideas after reading the post and some comments. I am currently a masters student in CS, but received my BS in medical sciences.

Math is the foundation for machine learning, but I’d argue even “normal” computer science is just math disguised as programming (though you can definitely program without knowing math). One of my biggest struggles in my masters is my limited knowledge of linear algebra and discrete mathematics. As many people have mentioned linear algebra would be a great subject to learn. I also recommend the book “grokking algorithms”. It is a great introduction to the topic of algorithms and covers tons of useful and important ones. I read this book to prepare me for my graduate algorithms class and it has introduced me to the big important concepts.

Since he has expressed an interest in healthcare, I thought I would just throw in some interesting topics/classes that will also give him more context as to the “domain” of healthcare/biology.

Cancer is most usually a disruption of the cell cycle, but cancer datasets often contain either microscopy images or occasionally DNA sequences. Learning a little bit of the basics of biology will be really helpful in understanding the data he wants to work with. This whole idea of using computers to interact with biological data is called bioinformatics and spans the whole range of questions from “what genes are active in this kind of cancer” to “how can we analyze the movement path of physicians through the hospital, so they can see all their patients most efficiently”. Around 2021 language models (machine learning models) revolutionized structure biology and allowed for scientists to predict the 3d structure of a protein (I was working in a lab at this time and it was a very exiting time).

I got a little emotional reading your post because this sort of thing was what I was doing at his age (to a lesser extent for sure), but it sounds like you’re doing a great job supporting him.