R is a language and environment for statistical computing and graphics. It is a GNU project similar to the S language and environment. R was developed at Bell Laboratories (formerly AT&T, now Lucent Technologies). R can be considered a different implementation of S. There are some important differences, but much code written for S runs unaltered under R. The R environment comprises an integrated suite of software facilities for data manipulation, calculation, and graphical display.
Uses of R Programming
Academics, scientists, and researchers use R to analyze the results of experiments. In addition, businesses of all sizes and in every industry use it to extract insights from the increasing daily data they generate.
Fintech
R is used at many fintech companies because money and statistics go hand-in-hand. Banks use the R language to create credit risk models and conduct other types of risk analysis. It is also used for fraud detection, mortgage modeling, volatility modeling, client assessment, and loan stress test simulations.
Research
The R programming language is widely used in academics and research. For instance, Cornell University teaches R in courses that require statistical computing. The University of California teaches students statistics and data analysis by introducing them to R, and many other universities do.
Retail
In retail and e-commerce, R is used for risk assessment and to create marketing strategies. For example, R's machine learning capabilities improve cross-selling and suggest better-related products at checkout to increase profits and sales. R is also used for sales modeling and targeted advertising in retail. Both Amazon and Flipkart use the R programming language for data analytics.
Government
The National Weather Service uses the R programming language to predict disasters and to forecast the weather. They also use the visualization features of R to create weather forecast images. In addition, the FDA uses R to evaluate drugs, perform pre-clinical trials, and predict possible reactions caused by the food products they review.
Data journalism
Data journalists use data to tell a story. They are journalists and data scientists who pull insights about our world and how we live from public data. This can be information from local government and police sources to tell a story about crime, financial data to show the state of a country's economy, or any other type of data that reveals an interesting pattern in how our world works. R is a popular language for data journalists because it allows them to find these insights and generate stunning graphics that tell the story.
Social media
Social media has always been a data-heavy industry. We are tracked everywhere we go online. Every action is stored in some database, waiting for an analyst to pull insights from it. Most social media sites' only profit source is their data on their users and targeted advertising. The R programming language is used for social media analytics, segmenting potential customers, and targeting ads.
Healthcare
R is heavily used in genetics, bioinformatics, drug discovery, and epidemiology. For example, in drug discovery, R is used to crunch the data gathered in pre-clinical trials and determine how safe a drug is. In epidemiology, R predicts how a disease will spread in a pandemic.
Manufacturing
Many companies use the R programming language to analyze customer feedback to help them improve the products they create. The Ford Motor Company uses R to analyze consumer sentiment about its vehicles and improve their design. Based on crop yield and other data, John Deere uses R to determine how many spare parts and products they need to produce.
R Programming Language Courses
There are many R programming learning resources online. But there are a few good quality courses that are available for free. Check out the best R programming certification courses, classes, tutorials, and online training. This list includes free and paid courses that beginner and expert-level learners can take. These are applicable for learning Data Science and Machine Learning and equally useful for anybody learning R programming in graphical and statistical fields.
R Programming Course A-Z™: R For Data Science With Real Exercises (Udemy)
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, and GGPlot2.
The course begins by teaching R programming basics and combining programming and statistical concepts. Then the course progresses to advanced topics like matrices and data frames. All the course material is intertwined with ample theory and real-life examples to support learning.
Course Highlights
- Create visualizations to capture your analysis best and captivate your audience
- Learn to solve real-life analytical challenges
- Learn how to customize R studio to suit your preferences
- Learn how to create and use vectors and matrices in R
- Learn how to install packages in R
- Practice working with financial, statistical, and sports data in R
- Know all about Normal distribution and Law of Large Numbers
- Homework exercises for extra practice
Data Science and Machine Learning Bootcamp with R (Udemy)
In this R language course, you will learn to program with R, use R for data analysis, create amazing data visualizations, and use Machine Learning with R. The program is suitable for experienced professionals who want to change their career track to data science and beginners who wish to learn data science and machine learning from the ground up.
This is a comprehensive R course with over 100 HD video lectures, detailed code notebooks for every lecture, eight articles, and three downloadable resources. It takes you through environment setup and the basics of programming in R, along with vectors, matrices, and data frames. Then it covers data visualizations in R leading to the data Capstone project. Further, the course delves into machine learning with a dozen portfolio projects. You get a certificate of completion on finishing the course.
Course Highlights
- Create Data Visualizations
- Use R to manipulate data easily
- Use R to handle CSV, excel, SQL files or web scraping
- Learn machine learning algorithms, including topics like Linear regression, Logistic regression, and more advanced topics such as decision trees, random forests, and support vector machines
- Variety of R programming exercises, capstone projects, and Machine Learning portfolio projects
- Access to online Q&A forum
- Explore data mining of Twitter for tending topics and creating a word cloud of these topics
R Programming Certification from Johns Hopkins University (Coursera)
This course aims to teach R as a programming language and how to use R for effective data analysis. It covers practical R programming issues, reading data into R, accessing R packages, writing R functions, debugging, profiling R code, and organizing and commenting on 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 is the basis for simulation studies.
Course Highlights
- Learn how to install and configure software necessary for a statistical programming environment
- Cover the history of R and S
- Learn to collect detailed information using the R profiler
- Understand programming language concepts and their implementation in R
- Make use of R loop functions and debugging tools
- Comes from a highly reputed university and highly acclaimed professors
Programming for Data Science with R Nanodegree Program (Udacity)
This Nanodegree program prepares learners for a career in Data science by teaching them the fundamental data programming tools of R, SQL, command line, and git. The introductory program is structured as a series of 3 courses – Introduction to SQL, Introduction to R Programming, and Introduction to Version Control. During the program, learners complete three projects focusing on the R language.
In the module on R programming, you will start by understanding common use cases of R and why it’s popular, along with installation & setup of the R Environment. You will learn to represent and store data using R data types and variables and use conditionals and loops to control the flow of programs. You’ll also learn about complex data structures like lists to store collections of related data. Additionally, you’ll learn to write your custom functions, write scripts, and handle errors. Data visualization using R libraries is also covered in depth.
Course Highlights
- Learn the most important programming languages (R and SQL) used by the data scientists
- Learn to make beautiful visualizations using the ggplot2 library
- Use the popular diamonds dataset to put your R skills to work
- Industry-relevant projects to gain hands-on experience
- Personalized feedback on projects from a network of 900+ project reviewers
- Get access to the student hub to connect with fellow learners
- Get access to technical mentor support and career support services
- No prior experience is required to enroll in the program
Data Science: 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. This edX R course aims to introduce learners to the basics of R programming. This course has no prerequisites, so it is suitable for anybody starting in the Data Science field. It is equally useful for anyone with programming experience in another language but who 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 free, but you must pay a small fee for graded exams and a certificate of completion.
Course Highlights
- Build a strong foundation to prepare for more in-depth courses
- Learn data wrangling with dplyr, data visualization with ggplot2, file organization with UNIX/Linux, version control with git and GitHub, and reproducible document preparation with RStudio
- Learn to perform operations in R, including sorting and making plots
- Learn to solve problems using a real-life dataset
R is the most popular language in the world of Data Science. It is heavily used in analyzing data that is both structured and unstructured. This has made R the standard language for performing statistical operations. R allows various features that set it apart from other Data Science languages. Learning R will have immense benefits that will provide you with the right tools to deal with data on a large scale.
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