Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Online Course

The R Programming Environment

Johns Hopkins University via Coursera

140
  • Provider Coursera
  • Cost Free Online Course (Audit)
  • Session In progress
  • Language English
  • Certificate Paid Certificate Available
  • Duration 4 weeks long
  • Learn more about MOOCs

Taken this course? Share your experience with other students. Write review

Overview

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.

Syllabus

Basic R Language
-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.

Basic R Language: Lesson Choices

Data Manipulation
-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.

Data Manipulation: Lesson Choices

Text Processing, Regular Expression, & Physical Memory
-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.

Text Processing, Regular Expression, & Physical Memory: Lesson Choices
-Choice 1: Get credit while using swirl | Choice 2: Get credit by providing a code from swirl

Large Datasets
-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.

Taught by

Roger D. Peng, PhD and Brooke Anderson

Help Center

Most commonly asked questions about Coursera

Reviews for Coursera's The R Programming Environment Based on 4 reviews

  • 5 star 25%
  • 4 star 0%
  • 3 star 25%
  • 2 star 25%
  • 1 star 25%

Did you take this course? Share your experience with other students.

Write a review
  • 1
Christian R
3 years ago
Christian completed this course.
0 person found
this review helpful
Was this review helpful to you? Yes
Alex I
3 years ago
Alex completed this course.
0 person found
this review helpful
Was this review helpful to you? Yes
Noah N
3 years ago
by Noah completed this course.
0 person found
this review helpful
Was this review helpful to you? Yes
Jawad R
3 years ago
by Jawad completed this course.
Was this review helpful to you? Yes
  • 1

Class Central

Get personalized course recommendations, track subjects and courses with reminders, and more.

Sign up for free

Never stop learning Never Stop Learning!

Get personalized course recommendations, track subjects and courses with reminders, and more.

Sign up for free