How to go from Newbie to R Programming Ninja
Programming isn't easy, especially if you're just getting started.
If you're coming into Data Science having started as a programmer, then it's not too bad, but if you're making the transition from one of the sciences or from statistics, then it can be a tall task.
I started out as a physicist and sort of accidentally became a Data Scientist (even before the term was known), and I had to learn how to program from scratch with no help at all. Just installing the program on your computer was a mammoth task back then. Sometimes you needed to do some programming to install the program so you could learn how to program!
It wasn't easy, but I got there.
Looking back I wish I'd had some help from someone who really knew what they were doing. Someone who could point me in the right direction.
These days there are lots of short cuts, plug-ins, packages and all sorts of things that can really help you make the best of your time, and this is where a programming language like R excels.
Despite being overtaken by Python as the most used programming language in Data Science, R is still one of the best languages to learn for Data Scientists.
It might not be as easy to learn as Python, but it has the advantage that it is superb for creating graphs and charts, and it has loads of ready-made packages to do pretty much whatever kind of statistical analysis you can think of (and a lot more besides).
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I'm not the person to help you with your programming quest. I can usually achieve the things I need to, but I'm still pretty awful at it - I'm embarrassed to show my code to a real programmer.
On the other hand, there are loads of video courses at Udemy dedicated to teaching the R programming language that are led by people who do know what they're doing.
If you're not sure how to get started with R or whether you're looking to improve your skill levels, these courses can help. I'm highlighting 6 of them here - the highest rated and most popular R courses at Udemy.
These instructors will help you with your first steps. Like installing R, writing your first program, installing packages, plotting some simple graphs and computing some statistics. You know - getting the confidence to know that it'll all be OK and that you really can do this. All the things that I didn't get when I first started...
Right now Udemy have a Black Friday offer on and these courses are deeply discounted. They are usually offered for up to £/$/Euro 200 but are on sale right now for a few days at just 10 £/$/Euro - so grab them while you can!
If you're reading this at some other time of the year, not to worry - Udemy have regular sales, so just click on through. If there isn't a sale on, just return here, register for our newsletter and we'll let you know whenever the sales are on.
A quick reminder - once you've enrolled for a particular course, you get lifetime access to it, even when the course is updated.
Top 3 Beginner R Courses at Udemy
These are the courses that I recommend if you're just getting started. They are great for beginners and will get you up and running in no time.
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Top 3 Advanced R Courses at Udemy
These are the R courses in Udemy that are for the not-quite beginner. They are more advanced, although you don't necessarily need to be at a more advanced level to take them. These courses are very popular, taught by Udemy superstars!
There are loads (over 1500) of R for Data Science courses at Udemy, not just the ones listed above. If none of these take your fancy, have a look around and I'm sure you'll find others that you might like.
Final word - when you've done any of these courses, please return and leave some feedback and a review in the comments below. If you loved the course, great - come and tell us. If you hated it, that's great too - leave a comment saying what you didn't like about it.
If you discover a better course out there, let me know - I may write about it in another blog post!
This blog post is part of a series on learning to be a Data Science Ninja - check out the other posts in the series below:
All 7 posts in the series:
- Learn to be a Data Science Ninja - The Easy Way
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