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Structure of an R course for beginners

I realize that this is a question that will probably not have a single best answer, and that it might be closed as such, but I think that this might get some very useful answers so maybe it can be turned into CW instead.

Suppose you have to give a course on R to complete beginners, and that you have limited time to do so so you need to make choices in what you emphasize. This is great, young innocent minds to bend to our will! But how do we do that?

How can we best setup an R course for absolute beginners so that they become efficient users of R. We want them to do everything right and efficient, but of course we want them to be able to do things in the first place even more. Some issues that come to my mind here are:

  • Indenting and using proper coding styles is very important. Should this be the first thing to come up? Even before looking at how to assign objects?
  • Loops vs applies vs vectorizations, what do you emphasize first? I think loops are so easy to learn and straightforward that those are nice to emphasize first, they might not produce very efficient code but they will be able to get things working! Then again, immediatly stressing vectorizations might get them to be more efficient in the long run.
  • Let them use RStudio from the beginning?
  • What would be a good order to introduce things?
question from:https://stackoverflow.com/questions/6411229/structure-of-an-r-course-for-beginners

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The number one thing you want to do in any short course is get students interested and motivated - you can convey very little information in 3-4 hours, but you can motivate your students to learn more. I'd recommend picking one topic of interest to your community and showing them how R can help them kick butt in that area. Cut ruthlessly - you want to figure out the absolute minimum path from knowing nothing about R to being able to do something useful, something that makes your students say "wow, that's cool". For me, I use graphics - in 3 hours you can teach the basics of ggplot2 (scatterplots, histograms, aesthetics and facetting) giving students a powerful toolkit for data exploration.

I would recommend using RStudio. I wouldn't recommend talking about code style, vectorisation, or probably even for loops.


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