I had to wonder if my alter ego was posting this question, but I knew it couldn't be me since because I'd been out of school for 30 years before returning last fall. Statistics is now a required course for CS at my school and took it first thing (the academic adviser signed me up) and I did struggle a bit because I couldn't follow the proofs involving calculus without help, but I still got an A (we didn't have to know the proofs for the exams). But when I saw the text (Pattern Recognition by Bishop) for the Machine Learning & Data Mining class the next quarter I knew I had to seriously (re)learn some calculus. I looked through a number of books and when I found Calculus for Dummies by Mark Ryan I knew I'd found exactly what I needed, the workbook is helpful too but not essential. Don't bother with Calculus II for Dummies though, it just an ordinary (which is to say useless for the non-naturals) calculus text (although I did pick up PDE from it in a brief look through).
And as it happens, the rules on AP Calculus transfer have also changed and I'm probably gonna wind up taking first year calculus anyhow, although pretty much too late for it to do me much good (it would have been helpful to do that before those classes I mention above). I will probably take it online from a community college rather than at the university though, which is what I'm also doing for the foreign language requirement. Thirty years ago the university didn't make CS majors take a foreign language reasoning that computer languages were foreign. We knew that was a joke then, of course the joke on me is that they fixed it in the interim.
For free online resources, the Kahn Academy videos are pretty good if that form works for you.
Don't listen to all the noise on in this thread. You're totally The Man for braving the slings and arrows in returning to school. It's actually pretty cool in a lot of ways. Among other things you get treated with a rather large measure of respect as a result of being old(er). That is probably on account of the kids thinking you're likely to be a professor or at least a grad student.