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The R Programming Environment

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The R Programming Environment

53,488 already enrolled

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Gain insight into a topic and learn the fundamentals.
4.3

1,167 reviews

Intermediate level
Some related experience required
Flexible schedule
3 weeks at 10 hours a week
Learn at your own pace
92%
Most learners liked this course
Gain insight into a topic and learn the fundamentals.
4.3

1,167 reviews

Intermediate level
Some related experience required
Flexible schedule
3 weeks at 10 hours a week
Learn at your own pace
92%
Most learners liked this course

Build your subject-matter expertise

This course is part of the Mastering Software Development in R Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • 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

There are 7 modules in this course

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.

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

1 video•Total 2 minutes
  • Welcome to the R Programming Environment•2 minutes
27 readings•Total 109 minutes
  • Course Textbook: Mastering Software Development in R•1 minute
  • Syllabus•10 minutes
  • Swirl Assignments•10 minutes
  • Datasets•10 minutes
  • Lesson Introduction•2 minutes
  • Evaluation•3 minutes
  • Objects•1 minute
  • Numbers•1 minute
  • Creating Vectors•1 minute
  • Mixing Objects•1 minute
  • Explicit Coercion•3 minutes
  • Matrices•3 minutes
  • Lists•2 minutes
  • Factors•4 minutes
  • Missing Values•3 minutes
  • Data Frames•3 minutes
  • Names•4 minutes
  • Attributes•1 minute
  • Summary•1 minute
  • The Importance of Tidy Data•5 minutes
  • The “Tidyverse”•4 minutes
  • Reading Tabular Data with the readr Package•10 minutes
  • Reading Web-Based Data•1 minute
  • Flat files online•10 minutes
  • Requesting data through a web API•10 minutes
  • Scraping web data•2 minutes
  • Parsing JSON, XML, or HTML data•3 minutes

What's included

1 assignment1 programming assignment

1 assignment•Total 180 minutes
  • Swirl Lessons•180 minutes
1 programming assignment•Total 180 minutes
  • Swirl Lessons•180 minutes

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

11 readings•Total 87 minutes
  • Basic Data Manipulation•10 minutes
  • Piping•7 minutes
  • Summarizing data•10 minutes
  • Selecting and filtering data•10 minutes
  • Adding, changing, or renaming columns•7 minutes
  • Spreading and gathering data•10 minutes
  • Merging datasets•10 minutes
  • Working with Dates, Times, Time Zones•3 minutes
  • Converting to a date or date-time class•7 minutes
  • Pulling out date and time elements•5 minutes
  • Working with time zones•8 minutes

What's included

1 assignment1 programming assignment

1 assignment•Total 180 minutes
  • Swirl Lessons•180 minutes
1 programming assignment•Total 180 minutes
  • Swirl Lessons•180 minutes

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

9 readings•Total 65 minutes
  • Text Processing and Regular Expressions•1 minute
  • Text Manipulation Functions in R•10 minutes
  • Regular Expressions•15 minutes
  • RegEx Functions in R•5 minutes
  • The stringr Package•10 minutes
  • Summary•1 minute
  • The Role of Physical Memory•10 minutes
  • Back of the Envelope Calculations•8 minutes
  • Internal Memory Management in R•5 minutes

Choice 1: Get credit while using swirl | Choice 2: Get credit by providing a code from swirl

What's included

1 assignment1 programming assignment

1 assignment•Total 180 minutes
  • Swirl Lessons•180 minutes
1 programming assignment•Total 180 minutes
  • Swirl Lessons•180 minutes

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

7 readings•Total 277 minutes
  • Working with Large Datasets•2 minutes
  • In-memory strategies•10 minutes
  • Out-of-memory strategies•10 minutes
  • Diagnosing Problems•5 minutes
  • How to Google Your Way Out of a Jam•5 minutes
  • Asking for Help•5 minutes
  • Quiz Instructions•240 minutes
1 assignment•Total 30 minutes
  • Reading and Summarizing Data•30 minutes

Earn a career certificate

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Instructors

Instructor ratings
4.0 (89 ratings)
Johns Hopkins University
37 Courses•1,689,551 learners
Johns Hopkins University
5 Courses•77,399 learners

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Learner reviews

  • 5 stars

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  • 4 stars

    24.85%

  • 3 stars

    7.71%

  • 2 stars

    3.34%

  • 1 star

    4.97%

Showing 3 of 1167

GG
·

Reviewed on Jun 10, 2020

Overall, it is an excellent course. However, there was a big difference in terms of difficulty between the quizzes, especially with the last one.

TS
·

Reviewed on Sep 13, 2021

Great Introduction, may we worth clarifying that for Data Manipulation the script must be saved before entering submit() as you cannot make progress.

MA
·

Reviewed on Nov 5, 2016

very well, structure, the quiz was admirably hard, but satisfying to work through and solve. you made me think outside the box, excellent

Frequently asked questions

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. 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.

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Financial aid available,