I decided to finish a couple of #RLang "tracks" before I refocus on the SQL and Python career tracks that I think will be most beneficial, and it has taken much, much longer than I expected.
R and many of its libraries are very inconsistent. But more importantly, few of their R-related courses start at the beginning and lay things out step-by-step. In fact, more than a year after I started with DataCamp was when I first ran into a course that did this. (It was amazing, and so far, I think I've encountered four of them. So finally, "aes" isn't some magic that I have to struggle to remember, it is the aesthetics of a graph / chart.)
So okay, when you take courses at your local community college, they set out the courses for each level based on levels. Learning C? There's an intro to C, followed by Intermediate C (which may be broken into multiple courses and using different names). There may also be an advanced C course. Most of them will have one or more prerequisites, so that you already understand the topics covered by those courses before you take the one you're interested in.
If you're taking the ACS (applied computer science ... may be computer information systems, management information systems, information systems management, information technology, or similar names) program, they'll have a list of which ones are required (which may have prerequisites).
Unfortunately, DataCamp isn't designed that way. It's rather haphazard, with three to fifteen four-hour courses arranged in one of around 30-40 "tracks" that mostly don't have prereqs arranged so that one has / acquires the underlying background before they take a course.
Other: DataCamp has a "pay per year" system which encourages people to take as many courses and tracks as they can and fails to encourage people to take time to do side projects using the skills their courses have covered. It may be good for them: We have X number of users, and most of them complete Y courses per year. It isn't good for their customer / students: No time to grab a few datasets, do some exploratory data analysis, then develop a hypothesis and go through the process to determine whether the dataset(s) support that hypothesis.
This morning, the rain seems to be steady. The dogs refused to go out this morning (post lightning / thunder; I know that if you hear thunder, you are close enough to be struck by lightning, so they don't even get offered the chance to go / stay outside during those times).
@fu@libranet.de They were "Indian Territory" at the time, but wedged between TX (CSA) and MO (USA, but some state leaders formed a rival CSA gov't in the SW corner until the union pushed them out), they were still right there in the thick of things.
When they became a state, riding right on the the top of Texas had to be a big influence.
@fu That's surprising at first, until one realizes it is the same kind of "Noble South" BS that many states down there teach.
They teach that wasn't the South that started the Civil War ("The War of Northern Aggression") by attacking a Union fort, it was the Union that started the war by not giving in on several contented issues (slavery was on the list, but they pretend they didn't start killing other White people over the belief that a few wealthy White landowners should own Black people.
Likewise, it wasn't that widespread but undocumented rumors of cheating in a closely observed election were not sufficient to overturn the election results, it was patriots on 2021-01-06 were not successful in persuading politicians to stop the election from being stolen.
For someone who was born hungry, I've never had to force myself to eat. But this week, I don't desire food, so if I eat, it is because I'm forcing myself.
A GNU+Linux bearing nomad migrating across a Windows-centric desert. I save the world from incompetent headquarters IT folks. I invite comment and discussion, but I dislike arguing.