You probably should have quoted me or copied the links or what have you, otherwise people would still need to search for my posts on random topics. I'm reproducing my post from Accessible PDF managers below. RA resource added. It's not a CS thing though. We're not required to take it, mostly because it's aimed at prooving Calculus. I also found the DE resource I used, seems like it migrated to a new website.
I can't guarantee if any of these will have alt texts, but for most cases you don't need image descriptions.
Here is stuff for Discrete Mathematics. Everything up to graphs should be fine, and even those might be okay. It depends on how much of a visual person you are. Most of the time when you're doing proofs you won't need to see those.
This is for Number Theory. It isn't a prerequisite a lot of the time, but Discrete Math kinda leaves you in a funny place regarding proofs. You hit a little of everything and don't talk about stuff that comes up often in CS because it's a basic proof course. Besides, you'll need Number Theory if you ever want to play with cryptography.
This is Calculus-based probability. I think it covers everything we learned and then some. Technically more, because it covers statistical inferencing as well. Be prepared to spend quite a bit of time on this one. You must know integrals (both single and multivariable) to get the most out of it. Solutions aren't available, but I did quite a bit of these so if you have questions either search or ask me. Try the former first because a lot of these have been previously worked by students on Math stack exchange.
Linear Algebra is right here. Be warned, the website is funny with navigation. Often sections collapse for some reason and you have to press enter on headings to expand solutions and/or examples. No big deal, but it can be off putting if you don't know it's a thing. This is mostly a computation-based book. You'll see proofs, but you shouldn't have to proove a lot on your own unlike with Discrete and Number Theory. I would recommend reading through Discrete first, however.
Abstract Algebra is highly recommended for us and I will be taking it in the Spring. THIS BOOK IS NOT A JOKE! You need Number Theory and Discrete for this one and likely some Linear Algebra, although if you do it'll be basic stuff like the vector dot product or something (which you should know from Calculus already). Super heavy on proofs. Barely any mindless number crunching. A single exercise can often take an hour or so--I'm not kidding!
Real Analysis is right here. This is typically not a CS course. In fact, a lot of Math majors don't even take it if they are not planning to do graduate work, which should tell you something about the difficulty of the course. Extremely tough. All proofs. Don't ask for help until Spring 2024, because that's when I'm set to take it. Even then I'm not sure if I would be able to. I've done a proof or two from the book and it was... rough.
Differential Equations requires a basic understanding of Calculus. You can probably get away with Calculus 1, but Calculus 2 wouldn't hurt here for some integration techniques. Our university requires basic multivariable Calculus, but only because we cover Fourier series near the end for solving partial differential equations. Take that as you will.
I have a better resource for Discrete, Number Theory, and Abstract Algebra, but that assumes you are willing to pay money. You do get alt text for Discrete and  number theory if you pay, though. Let me know if you're interested.
Edit: I had good luck with Bill Kinney on YouTube. His Differential Equations with Linear Algebra playlist is here, and Abstract Algebra videos are here. I don't like him for Calculus though, that goes to Professor Leonard. If you ever take Calculus 3, which you should because it serves as a foundation for a lot of other courses, I would highly recommend him. He has calculus one and two videos as well. Very easy to understand and follow along with, although people said to me that his videos are long. True, but when you finish, and if you actually pay attention, you will be set for pretty much any problem on that topic.

@10, you'll always be working on your presentation of proofs. Always. Proof writing is super super hard beyond trivial classroom cases. Most real world proofs end up... messy for the lack of better term.
As for my exams, it honestly depends. I never took one orally. You need to talk with your professor to discuss your options. Some of my professors reserved a room for all the people with extra time and I just took it with them. Others made me set up a test through the official system, which was a major major pain. No right answer here.
@12, resources, one per subject. Rosen's Discrete Mathematics is one of them. Fantastic book that covers waaaay more than the link in post 2. Rosen also wrote Elementary Number Theory 6th Ed, which is one of my favorites because it's as clear as a book about proofs can be. It's very easy to follow and it, again, has a lot of material on all sorts of things related to number theory. Abstract Algebra resource is here. I like this one particularly because of its applications of concepts. It's not just straight up prove prove prove all day. And it's like a history tour, too, which I find rather interesting.

I'm not a Math guy. Far from it. I would've never thought it possible to do some of these kinds of things because graphs are the absolute bane of our Mathematical existence as blind people and no exaggeration. But I gotta admit, it is interesting.

I read the introduction to the discrete mathematics book that you provided. Definitely interesting what you can do with it at the very least even if I'm not the most intelligent person when it comes to Math. Just for context, we skipped geometry because the high school said it'd  be too expensive to provide the equipment needed for us to do 3-dimentional shapes and things like that. So yeah, I have literally no geometry knowledge.

Your link seems to be broken. Also, the one that I had has alternative text for images. Not a necessity, but nice when you talk about logic circuits and/or graphs.