According to 2017 Burtch Works Survey 40% of surveyed data scientists prefer R. It is undoubtedly the most popular language used by the data scientists around the world. Data Science technologies have transformed the way analysts used to mine the data. R programming language is one such leading data science technology.

R is a software environment and a programming language that was specifically created for statistical computations and graphical applications. Now becoming the leading tool for machine learning, data analysis & visualization and statistics, It has a gained a lot of traction since its inception. With major boom in big data, a lot of data science job opportunities are getting created every day and expertise in R programming will assist you in taking your career as data scientist to the next level.

## R For Data Science With Real Exercises

This is one of the best R programming tutorials that help you master programming in R and R studio with live examples. You will learn data analytics, data science, statistical analysis, packages, functions, GGPlot2.

More than 96,000 students have taken this Udemy R course. The course does not assume any prior knowledge or experience. It is designed in such a way that you can succeed at it even without any statistical background. It takes you step-by-step through the steep learning curve of R. You will be using specifically designed datasets to practice the skills you learn in the course.

The course begins with teaching R programming basics and how to combine programming and statistical concepts. Then the course progresses to advanced topics like matrices and data frames. All the course material is intertwined with ample of theory and real life examples to support learning. You will learn a new valuable skill in every single tutorial and in every section you will understand how you can apply that skill to solve real world problems.

## Data Science and Machine Learning Bootcamp with R

In this R language course you will learn how to program with R, how to use R for data analysis, how to create amazing data visualizations, and how to use Machine Learning with R. The course has been developed and is taught by Jose Portilla who is one of the best instructors on Udemy and has taught thousands of students about Data Science and Programming. The program is designed to be suitable for both experienced professionals who want to change career track to data science and complete beginners who wish to learn data science and machine learning from ground up.

This is a very comprehensive R course with over 100 HD video lectures, detailed code notebooks for every lecture, 8 articles and 3 downloadable resources. It takes you through environment setup to begin with and then the basics of programming in R along with vectors, matrices and data frames. Then it covers data visualizations in R leading to data Capstone project. Further, the course delves into machine learning with a dozen of portfolio projects. You get a certificate of completion on finishing the course.

## R from Johns Hopkins University (Coursera)

This course is a part of Data Science Specialization from Johns Hopkins University. It is aimed at teaching R as a programming language and how to use R for effective data analysis. It covers practical issues in programming in R, reading data into R, accessing R packages, writing R functions, debugging, profiling R code, and organizing and commenting R code.

This Certification in R programming starts with basic building blocks of R like datatypes, functions to read and write data etc. Then it proceeds to formulate how to write R programs using control structures, R functions and basic operations on data. You will also learn about code profiling and debugging. The course also explores how to simulate data in R, which serves as the basis for doing simulation studies.

The course is instructed by Roger D. Peng, PhD, Associate Professor, Biostatistics; Jeff Leek, PhD, Associate Professor, Biostatistics and Brian Caffo, PhD Professor, Biostatistics.

## R Basics Certificate by Harvard University (edX)

This is the first course in the 9-part Data Science professional certificate program offered by HarvardX on the edX platform. The goal of this edX R course is to introduce learners to the basics of R programming. This course has no prerequisites so it is suitable for anybody making a start in Data Science field. It is equally useful for anyone who has programming experience in another language, but would like to learn R programming.

This R programming certification course uses a real-world dataset about Crime in the United States to teach how to solve real problems using R. It covers R’s functions and data types, vector operations and advanced functions like sorting. You’ll learn how to apply general programming features like conditional construct “if-else,” and “for loop” commands, and how to wrangle, analyze and visualize data

The course instructor Rafael Irizarry does a great job explaining topics in plain language making even complex topics very easy to understand. There are several programming assignments to solidify the learning. The course is available for free but you need to pay a small fee for graded exams and certificate of completion of course.

## Statistics with R Certification by Duke University (Coursera)

Statistics with R certification is one of the best courses to master statistics with R. You will learn to analyze and visualize data in R and create reproducible data analysis reports.

This R statistics specialization includes 5 courses – Introduction to Probability and Data, Inferential Statistics, Linear Regression and Modeling, Bayesian Statistics and Statistics with R Capstone. The capstone project will be an analysis using R that answers a specific scientific/business question provided by the course team. The dataset for analysis will be provided to learners and they will need to apply various methods and techniques learnt in the previous courses.

Dr. Mine Çetinkaya-Rundel is the main instructor of the program along with three other Professors from the Duke University’s Department of Statistical Science. No programming experience is needed to take this program, just knowledge of basic maths and a genuine interest in data analysis.

## Advanced Analytics In R For Data Science (Udemy)

If you have basic knowledge of R programming language and want to take your skills to the next level, then this is the best R programming course for you. It focuses on data science & analytics and statistical analysis in R language. The instructor Kirill Eremenko takes you through the complex concepts in quite simplified and easy to understand manner.

The course consists of 51 lectures that cover Data preparation, Lists in R and “Apply” family of functions in detail. You will learn how to prepare data for analysis in R, perform median imputation method, work with date-times in R, how to use lists in R, how to use apply functions instead of loops, how to nest user defined functions with apply-type functions etc.

This course is not for complete beginners, and assumes basic knowledge of R. Knowledge of GGPlot2 package, dataframes, vectors and vectorized operations is also recommended.

## Statistics with R – Beginner Level (Udemy)

This course on Udemy focuses on basic statistical analyses using R programming language. You will learn how to manipulate data in R and prepare it for the analysis – filtering your data frame, recoding variables and computing new variables. Also learn about computing the main statistical figures in R – mean, median, standard deviation, skewness, kurtosis etc., and data visualization using tables and charts.

The course includes 3 hours on-demand video, 13 articles and 12 downloadable resources and comes with full lifetime access. Though this is a brief course, it covers essential concepts thoroughly with examples for illustration. Large variety of data frames are provided for practice, along with notes and R files. This is a beginner level course and assumes knowledge of basic statistics.

## Mastering Software Development in R Certification

This specialization in R programming provides rigorous training in R language and also teaches the best software development practices for building data science tools that are not only robust, modular and reusable but also collaborative (thus suitable for use in team based and community environments). Through this program you will gain necessary skills for handling complex data, building R packages and developing custom data visualizations.

This R language certification program comprises of 5 courses. It starts with an introduction to R (essential foundational concepts of R) and then moves on to advanced topics like functional programming, object-oriented programming, error-handling, user-functions, R packages and software maintenance. It ends with a Capstone project in R programming. You will find that throughout the program, the focus is on aspects of R language that are useful for creating tools and code that can be used by others.

The course assumes some programming experience (in any language) and working knowledge of mathematics up to algebra.

## Learning – Lynda

This is a beginner level course that introduces you to the R programming language. It starts with instructions on installation of R, setting up the R environment and using R Studio. Then it proceeds to cover how to read data from spreadsheets & SPSS, how to use and manage packages for advanced R functions.

The instructor of this course is Barton Poulson who is a professor, designer and data analytics expert. He effectively takes you through several examples on how to create charts and plots, check statistical assumptions and the reliability of your data, look for data outliers, and use other data analysis tools.

## R Programming for Statistics and Data Science (Udemy)

This R Certification program is the most comprehensive introduction to R programming for Statistics and Data Science. The aim of this course is to progress you from being a complete beginner in R language to an expert professional who can take up data manipulation on demand. You will be exposed to fundamentals of programming, data manipulation techniques and tools, and data visualizations and plots. It also includes a step-by-step guide to statistics.

This R programming class is a very good blend of theory and practice. It takes care to incrementally build your theoretical knowledge and practical skills. Multiple exercises included in the course help to reinforce your learning. It also includes homework and projects to further challenge the learners. On completion of the course, you will receive a verifiable certificate.