Hello all. Just started learning R from the google analytics course on coursera. Their course on R is fun and engaging. I am almost done with the course, and my next step is to finish the R for data science book.
My question is that is this a good approach to learn R and become proficient in it? Any suggestions or comments? Thank you
After you've finished R4DS, it may be useful to find some data to just play around with and start asking your own data science questions! When new R users have had some good initial instruction, I normally tell them to just have a go at their next project using R rather than Excel or their usual tools.
If you're not in the position to do that (if you're not in a data profession, or your work is weird about using different tools, or you just can't commit to R in a professional space right now), consider the #tidytuesday data project:
Every week there's a new data set to have a go at analysing, and a supportive twitter community based around sharing analysis, visualisations and code. I personally learned a lot from playing around with these fun data sets and reading other R users' #tidytuesday GitHub repos.
Some good ones to have a look at to see the cool stuff people have done in R are:
Awesome! Thank you so much for this great advice.
Definitely gives me direction on what to do once I am done with the R4DS book.
Same as Jack: practice.
Trying to answer questions on forums like this one is also a good way to get thinking about hard problems.
There are also websites with exercises in several fields: codewars.com for programming/algorithms, rosalind for bioinformatics (which involves a lot of string processing, some math and stats), and of course Kaggle for machine learning. It's particularly useful when once you did solve a problem, you can see what other people used (and typically there will be some high quality code there).
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