I took Python for Everybody and it was a very good introduction. There's a Python for Data Science (also from U Mich) that apparently is pretty good too: https://www.coursera.org/specializations/data-science-python
Another good class I took prior to the OMSA was Mathematics for Machine Learning (a three-course specialization): https://www.coursera.org/specializations/mathematics-machine-learning
It was very helpful to have a general idea of what Machine Learning is and a good refresher of Linear Algebra and Calculus.
I have heard pretty good comments from this class: https://www.edx.org/course/linear-algebra-foundations-to-frontiers
They use Matlab (which is one of the two programming languages you can use in the ML class, so it would be nice to have that skill).
Apparently the hardest compulsory class of the program is Data and Visual Analytics which has 4 50-60-hour projects your are meant to finish in 3 weeks each. So you will need to quickly understand tools such as SQL (https://www.coursera.org/specializations/learn-sql-basics-data-science), Linux Command Line (https://www.coursera.org/courses?query=linux%20commands), D3.js (https://www.coursera.org/specializations/information-visualization), among others in the cloud.
In general I agree that most of what is taught during the master can be learned on each class as their are self-contained, but being prepared in advance can help you have a better experience and learn more in-depth content.
All the best!