Because DataCamp is known for welcoming sexual harrassy behavior and their CEO seems like a child, here are some alternative recs about cleaning and the other stuff that makes up 95% of data jobs:
here's what to look for, every time: https://twitter.com/b0rk/status/1182288624018247685
here's a coursera course on it: https://www.coursera.org/learn/data-cleaning
here's how SQL works: https://twitter.com/b0rk/status/1184571894722449409
here's how tidyverse works, including various read/write libraries + opinions on data types + code reusability that are generally applicable: http://r4ds.had.co.nz/
hopefully a helpful (+ free) set of alternatives!
I'd also say hard choices around interpolation vs exclusion seem hard to find material on, probably because so data/resource/context specific, but also good to be aware of.