Top 5 Free Courses to Learn R Programming for Data Science and Statistics in 2020

Original article was published on Becoming Human: Artificial Intelligence Magazine

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More and more programmers are learning the R programming language to become a Data Scientist, one of the hottest and high paying technical jobs on the planet.

Even though I am from the Python camp, when it comes to choosing between Python and R for Data Science, Machine Learning, and Artificial Intelligence, mainly because of the excellent libraries like TensorFlow Python offers, I had tried R for a short time.

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If you are also on the same boat and want to try or learn R programming for Data Science and Machine learning purpose and looking for some excellent free courses to start your journey, then you can take some ideas from this article.

In the past, I have shared some machine learning courses on Python, and today, I am going to share some of the free courses to learn R programming language as well as Data Science and Deep Learning using R.

Btw, for those, who are not familiar with R, it’s a programming language and a free software environment popular among statisticians and data miners for developing statistical software.

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R burst into the scene with its robust support for stats (linear and nonlinear modeling, classical statistical tests, time-series analysis, classification, clustering, …) and graphical techniques. Still, in recent years, it has gained a lot of popularity among Data Scientist and Data minors.

Along with Python, R is the second most popular language to learn the new world of Data Science, Machine Learning, Deep Learning, and Artificial intelligence.

5 Free R Programming Courses for Data Scientists and Programmers

When you look for free R tutorials and courses, you will find a lot of classes, but most of them are neither complete nor up-to-date. There are very few excellent quality courses and tutorials that are freely available.

This article is a collection of such free R programming courses. I compiled this list for learning Data Science and Machine learning with R,. Still, this list is equally useful for people learning R programming for statistics and graphics purposes, which is another strength of this excellent programming language.

Anyway, without any further ado, here is my list of some of the best, free online courses to learn R programming language.

1. R Programming by Johns Hopkins University

This is one of the best and excellent course to get a general overview of the R programming language in Coursera , and I strongly suggest you go through this course before starting with any other class.

Like many Coursera courses, this is also free if you want to learn and explore, but you need to pay if you wish to a certificate as well. It won’t take much time to finish, and you will learn both the historical background of R as well as where does it stand now.

This course will make you familiar with the R programming language; it’s terminology, features, syntax, and other stuff.

2. R Basics — R Programming Language Introduction

This is another free R programming course from Udemy and perfect for learning R programming from scratch.

The course contains more than 4 hours of content and 2twoarticles. Its step by step approach is great for beginners and Martin has done a wonderful job to keep this course hands-on and simple.

You will start by setting up your own development environment by installing the R and RStudio interface, add-on packages, and learn how to use the R exercise database and the R help tools.

After that, you will learn various ways to import data, first coding steps including basic R functions, loops, and other graphical tools, which is the strength of R

The whole course should take approx. 3 to 5 hours to finish, and there are exercises available for you to try out whatever you have to learn in R. You will also get access to the Martin Code (The instructor) is using for the demos.

In short, one of the best free courses to learn R programming in 2020.

R Basics – R Programming Language Introduction | Udemy

3. Learn Data Science With R

This is the R programming course which will introduce Data Science with R. It has over 8.5 hours of material and touches most of the R concepts which are useful for Data scientists.

You will learn basics of Data Science like what is Data Science, data types, Vectors, Factors, List, Matrices, Data Frames, and Reading Data from files, Oracle Data using RJDBC, RODBC, and ROracle.

The Instructor Ram Reddy is a Data scientist himself and founder of RRITEC, a company dedicated to helping scientists better understand and visualize their data.

Though the course is good in terms of understanding fundamentals of both R and Data Science, it lacks some real-world examples and business scenarios, which you can find on @Kiril Eremenkoon’s R Programming A-Z™: R For Data Science With Real Exercises! course.

If you can spend a couple of dollars then that is the best resource to learn Data Science with R. You can grab this course on just $9.9 which is fully worthy of your money.

R Programming A-Z: R For Data Science (Course & Exercises)

4. Learn R for Business Analytics from Basics

Apart from Statistics, Graphics, Data Science and Machine Learning, R is also growing on the Business Analytics platform. It’s possible that R may become one of the most used Business Analytics tools in nature future.

It is giving strong competition to giants like SAS, SPSS, and other erstwhile business analytics packages.

If you are someone who wants to learn Business Analytics and want to leverage R’s capability then this is the perfect course for you.

As the instructor says this course is designed specifically for someone who knows the basics of Business Analytics and wants to learn the implementation of those skills on the R platform.

In this course, you will learn how to download and install R programming packages, IDE like RStudio. You will also learn how R can be leveraged in Business Analytics.

The course is also hands-on and you will learn how to import Data in R and perform exploration and transformation activities, perform bivariate analysis and plot charts in R to understand data distribution and run correlation and regression in R to analyze model results.

5. R, ggplot, and Simple Linear Regression

This is rather old but one of the most popular free R programming courses on Udemy which will teach you Data Science with R.

In this course, you will learn how to start with R programming and use the excellent graphics package for R, ggplot2. Along the way, you will also learn Data Science concepts like the basics of simple linear regression.

There are no prerequisites, so anyone interested in R, ggplot or data science and join this course.

The course starts with the installation of R and RStudio and then explains R and ggplot skills as they are needed when you progress toward an understanding of linear regression.

That’s all about some of the best free courses to learn R Programming language, particularly for Data Science and Machine learning. It’s true that many programmers are learning R for just those two reasons, R has other advantages as well, particularly on statistics. If your job involves a lot of statistics and graph work, R could be a good tool in your arsenal.

Btw, If you don’t mind paying $10 bucks then R Programming A-Z™: R For Data Science With Real Exercises! is the BEST course to learn R for Data Science.

R Programming A-Z: R For Data Science (Course & Exercises)

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Closing Notes

Thanks, You made it to the end of the article … Good luck with your R Programming journey! It’s certainly not going to be easy, but by following this roadmap and guide, you are one step closer to becoming the Data Scientist you always wanted to be.

If you like this article, then please share it with your friends and colleagues, and don’t forget to follow javinpaul on Twitter and of course (javinpaul) on Medium!

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Top 5 Free Courses to Learn R Programming for Data Science and Statistics in 2020 was originally published in Becoming Human: Artificial Intelligence Magazine on Medium, where people are continuing the conversation by highlighting and responding to this story.