Weird feeling for me: In a few of these #DataCamp courses, I'm now feeling lost when I'm doing the exercises. I think I need to spin up a separate data analysis project using #R-Lang, or #Python + #numpy + #pandas or #SQL ... or maybe do the same project three ways.

With SQL, at least, it seems to be an artifact of the way their hands-on code runner works (Displays a short `head` of the relevant tables ... so when you're working on queries, you may not have a direct way to see whether your query does specifically what you expected and intended.)

With R-Lang, it is just that it isn't always apparent what the language will do. Some things are inexplicably backwards compared to most other languages I've seen, so mentally I tend to go with the wrong choice. Also, the practice question set is too small. I've reached the point where some of the practice exercises are familiar enough that I know which answer to choose immediately without having any understanding of why that is the correct choice.