This course provides a rigorous introduction to the R programming language, with a particular focus on using R for software development in a data science setting. Whether you are part of a data science team or working individually within a community of developers, this course will give you the knowledge of R needed to make useful contributions in those settings. As the first course in the Specialization, the course provides the essential foundation of R needed for the following courses. We cover basic R concepts and language fundamentals, key concepts like tidy data and related "tidyverse" tools, processing and manipulation of complex and large datasets, handling textual data, and basic data science tasks. Upon completing this course, learners will have fluency at the R console and will be able to create tidy datasets from a wide range of possible data sources.
Give your career the gift of Coursera Plus with $160 off, billed annually. Save today.
The R Programming Environment
This course is part of Mastering Software Development in R Specialization
Instructors: Roger D. Peng, PhD
52,219 already enrolled
Included with 
(1,162 reviews)
Skills you'll gain
Details to know
Add to your LinkedIn profile
4 assignments
See how employees at top companies are mastering in-demand skills
Build your subject-matter expertise
- Learn new concepts from industry experts
- Gain a foundational understanding of a subject or tool
- Develop job-relevant skills with hands-on projects
- Earn a shareable career certificate
Earn a career certificate
Add this credential to your LinkedIn profile, resume, or CV
Share it on social media and in your performance review
There are 7 modules in this course
In this module, you'll learn the basics of R, including syntax, some tidy data principles and processes, and how to read data into R.
What's included
1 video27 readings
What's included
1 assignment1 programming assignment
During this module, you'll learn to summarize, filter, merge, and otherwise manipulate data in R, including working through the challenges of dates and times.
What's included
11 readings
What's included
1 assignment1 programming assignment
During this module, you'll learn to use R tools and packages to deal with text and regular expressions. You'll also learn how to manage and get the most from your computer's physical memory when working in R.
What's included
9 readings
Choice 1: Get credit while using swirl | Choice 2: Get credit by providing a code from swirl
What's included
1 assignment1 programming assignment
In this final module, you'll learn how to overcome the challenges of working with large datasets both in memory and out as well as how to diagnose problems and find help.
What's included
7 readings1 assignment
Instructors
Offered by
Recommended if you're interested in Data Analysis
Coursera Project Network
University of California, Santa Cruz
University of Michigan
University of Cape Town
Why people choose Coursera for their career
Learner reviews
Showing 3 of 1162
1,162 reviews
- 5 stars
59.38%
- 4 stars
24.95%
- 3 stars
7.65%
- 2 stars
3.27%
- 1 star
4.73%
New to Data Analysis? Start here.
Open new doors with Coursera Plus
Unlimited access to 7,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription
Advance your career with an online degree
Earn a degree from world-class universities - 100% online
Join over 3,400 global companies that choose Coursera for Business
Upskill your employees to excel in the digital economy
Frequently asked questions
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.