I haven't come across a pre-ML certificate per se, but mostly because almost all of what you need for pre-ML is taught in college at the sophomore-ish/junior-ish level.
If you're looking for formal coursework, at a minimum you should have:
- Basic introductory computer science sequence (OOP through data structures)
- Freshman/sophomore Calculus sequence through vector calculus (partial derivatives, gradients, etc)
- Linear Algebra through eigenstuff
- Calculus-based Statistics through regression
Since you're looking for in-person classes, any of that you haven't taken already is available at the community college level. (In NYC, that even includes the Calculus-based Statistics, which is usually junior-level.)
There's a book, Mathematics for Machine Learning and an accompanying Coursera course, that covers the calculus and linear algebra you'll need without all the cruft that's only relevant for like math majors and structural engineers, but I felt like their handling of vector calculus was a bit rushed and wound up taking Calc III at a community college instead.
The further you can go beyond that, the more you'll understand what you're looking at when it comes time to start reading papers - algorithm analysis, numerical analysis, real analysis, regression analysis...
(PS: Be wary of anyone who says you can just jump right in from 0 without building the foundation first. You can, kind of, from a computer science perspective, but without the math background, you'll be calling functions you don't really understand to build models you don't really understand, and doing the intellectual equivalent of throwing darts to debug your code or improve your models.)