Learn R
Learn how to code and clean and manipulate data for analysis and visualization with the R programming language.
Skill level
BeginnerTime to complete
Average based on combined completion rates — individual pacing in lessons, projects, and quizzes may vary14 hoursProjects
10Prerequisites
None
About this course
R is a widely used programming language that works well with data. It’s a great option for statistical analysis, and has an active development community that’s constantly releasing new packages, making R code even easier to use. It’s built around a central data science concept: The DataFrame, so if you’re interested in data science, analysis, and visualization, you’ll want to learn how to use R.
Skills you'll gain
Write code in R
Organize, edit, and clean data
Create data visualizations
Syllabus
16 lessons • 10 projects • 10 quizzesCertificate of completion available with Plus or Pro
Earn a certificate of completion and showcase your accomplishment on your resume or LinkedIn.
Projects in this course
- practice Project
Blood Transfusion Analysis
In this project we will be using statistical techniques to make statements and draw conclusions about a blood tranfusion company's userbase. - practice Project
Calculating Population Change Over Time with R
In this project, you will learn how to use the basics of R syntax and operations to make calculations. - practice Project
Explore the 1985 Cars Dataset
Use your knowledge of DataFrames, reader, and dplyr to explore this dataset about cars from 1985.
Earn a certificate of completion
Show your network you've done the work by earning a certificate of completion for each course or path you finish.- Show proofReceive a certificate that demonstrates you've completed a course or path.
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Learn R course ratings and reviews
- 5 stars
- 4 stars
- 3 stars
- 2 stars
- 1 star
- Great course to start learning how to code in R and to gain basic (and not so basic) knowledge about statistics at the same timeIngrid S.Verified Learner
- This course was incredibly easy to follow along with. The practice exercises within the lesson were very helpful!Lindsay A.Verified Learner
- It's a really comprehensive course and teaches you the basics of using R from no knowledge of programming beforehand. When you get stuck, the tips and solution may be able to help you understand what went wrong.Jin-Ying N.Verified Learner
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Frequently asked questions about R
R is an open-source programming language designed for data science and statistics. It’s a powerful tool for working with data, and its documentation and supportive community offer helpful resources for new programmers.
Should I Learn R?
If you are new to programming and trying to decide where to start, the choices can seem endless. There are so many programming languages to choose from. How do you know which one is for you?
The R programming language may be one of the languages you ran into in your search. And you might be wondering if R is the language for you. To help you decide, let’s take a look at why someone would want to learn R, what it is used for, and how easy it is to learn.
Join over 50 million learners and start Learn R today!
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Related resources
- Article
R Programming Language Explained (Careers, Use Cases, Difficulty)
Explore what the R programming language is, its features, pros and cons, use cases, careers, and how it compares to Python. Learn how R is used in data science and how easy it is to learn. - Article
Hands-on Statistics with NumPy in Python
Learn how to calculate measures of central tendency like mean, median, and weighted mean, and measures of spread like range, variance, and standard deviation using the NumPy module in Python. - Article
Intro to Data Acquisition
Exploring and defining the methods of obtaining data
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Practice Projects
Guided projects that help you solidify the skills and concepts you're learning.Assessments
Auto-graded quizzes and immediate feedback help you reinforce your skills as you learn.Certificate of Completion
Earn a document to prove you've completed a course or path that you can share with your network.