I think there's a free entry level course on coursera that doesn't require a lot of math. The book Introduction to Machine Learning with Python: A Guide for Data Scientists doesn't need a lot of math either. I got it on an old humble bundle.
You can get a lot of help nowadays when using frameworks, such as Keras. However, it is good to know the math in order to understand how things work. Would recommend taking a (online) course in linear algebra and statistics.
For applied black-box machine learning, you need statistics (sampling, populations, and so on).
To understand deeper about the algorithms, you need probability and linear algebra, and multivariable calculus.
I'm taking artifical intelligence at uni right now - i've only ever completed basic calculus courses and a handful on propositional logic
you can definitely skip alot of the background knowledge with some of the publicly available frameworks, but if you start getting bugs its alot harder to understand whats going wrong