R programming language has gained much traction over the last few years when it comes to processes of data analytics and visualizations. With better visualization techniques, this programming language has an essential role in statistical methods.
In this article, we list down eight online resources which are freely available to learn the popular R language.
Table of contents
1. R Programming
This course will help you understand how to program in R and how to use it for effective data analysis. You will learn how to install and configure software necessary for a statistical programming environment. The course covers practical issues in statistical computing, which includes programming in R, reading data into R, accessing R packages, writing R functions, debugging, profiling R code, and organizing and commenting R code.
Source: Coursera
2. Introduction To R For Data Science
This introduction to R programming course will help you master the basics. There are seven sections, where you will cover basic syntax and data analysis using R. Starting from variables and basic operations, you will learn how to handle data structures, such as vectors, matrices, data frames and lists, graphical capabilities of R and learn steps to create data visualizations.
Source: edX
3. R Basics – R Programming Language Introduction
This is a beginners course, where you will learn about the basic structure of R, including packages, how to navigate in the RStudio interface, how to make basic graphs, how to perform basic commands in the R programming language, as well as how to handle packages, and how to use R help tools, and more.
Source: Udemy
4. Data Science: R Basics
This course will introduce you to the basics of R programming, and learn the R skills needed to answer essential questions around a practical example on differences in crime across different states. You will also learn R’s functions and data types, tackle how to operate on vectors and when to use advanced functions like sorting, how to apply general programming features, as well as how to wrangle, analyze and visualize data.
Source: edX
5. Introduction To R
This course is provided by DataCamp, where you will learn the basics of data analysis by manipulating common data structures, such as vectors, matrices, and data frames. The course includes an introduction to R, vectors, matrices, factors, data frames, list and much more.
Source: DataCamp
6. Learn R For Business Analytics From Basics
This course is meant for those who understand the basics of Business Analytics and want to gain insights on the implementation of those skills on the R platform. You will learn how to perform all the analytical tasks required to develop a ‘Losses prediction model in R’ from scratch, how R can be leveraged in business analytics, how to load important packages into R, perform bivariate analysis and plot charts in R to understand data distribution, run correlation and regression in R, analyze model results, and more.
Source: Udemy
7. Learn R
In this course, you will learn the fundamental programming concepts in R language. After the basics, you will learn how to organize, modify and clean data frames, how to create data visualizations to showcase insights in data, and more. The tutorial includes an introduction to R, data frames, data cleaning, fundamentals of data visualization with ggplot2, among others.
Source: Code Academy
8. R Tutorial
Source: Cyclismo
In this tutorial, you will learn about the basics of the R language. It includes basic data types, basic probability distributions, basic plots, plotting, data visualization, data management, time data types, linear least squares regression, and more.
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