About this Specialization
9,279 recent views

100% online courses

Start instantly and learn at your own schedule.

Flexible Schedule

Set and maintain flexible deadlines.

Beginner Level

Approx. 3 months to complete

Suggested 7 hours/week

English

Subtitles: English, Chinese (Simplified), Arabic, French, Vietnamese, Georgian, Estonian, German, Thai, Japanese, Nepali...

What you will learn

  • Check

    Build R packages

  • Check

    Custom data visualization and graphics

  • Check

    Data manipulation and wrangling

  • Check

    Produce and scale data science products

Skills you will gain

R ProgrammingData Visualization (DataViz)Ggplot2tidyverseObject-Oriented Programming (OOP)

100% online courses

Start instantly and learn at your own schedule.

Flexible Schedule

Set and maintain flexible deadlines.

Beginner Level

Approx. 3 months to complete

Suggested 7 hours/week

English

Subtitles: English, Chinese (Simplified), Arabic, French, Vietnamese, Georgian, Estonian, German, Thai, Japanese, Nepali...

How the Specialization Works

Take Courses

A Coursera Specialization is a series of courses that helps you master a skill. To begin, enroll in the Specialization directly, or review its courses and choose the one you'd like to start with. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. It’s okay to complete just one course — you can pause your learning or end your subscription at any time. Visit your learner dashboard to track your course enrollments and your progress.

Hands-on Project

Every Specialization includes a hands-on project. You'll need to successfully finish the project(s) to complete the Specialization and earn your certificate. If the Specialization includes a separate course for the hands-on project, you'll need to finish each of the other courses before you can start it.

Earn a Certificate

When you finish every course and complete the hands-on project, you'll earn a Certificate that you can share with prospective employers and your professional network.

how it works

There are 5 Courses in this Specialization

Course1

The R Programming Environment

4.4
858 ratings
221 reviews
Course2

Advanced R Programming

4.3
407 ratings
100 reviews
Course3

Building R Packages

4.2
174 ratings
44 reviews
Course4

Building Data Visualization Tools

4.0
125 ratings
31 reviews

Instructors

Avatar

Roger D. Peng, PhD

Associate Professor, Biostatistics
Bloomberg School of Public Health
Avatar

Brooke Anderson

Assistant Professor, Environmental & Radiological Health Sciences
Colorado State University

About Johns Hopkins University

The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world....

Frequently Asked Questions

  • Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate, or you can audit it to view the course materials for free. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.

  • This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.

  • Time to completion can vary based on your schedule, but most learners are able to complete the Specialization in 3-6 months.

  • Some programming experience (in any language) is recommended. We also suggest a working knowledge of mathematics up to algebra (neither calculus or linear algebra are required).

  • We strongly recommend that you take the courses in order.

  • Coursera courses and certificates don't carry university credit, though some universities may choose to accept Specialization Certificates for credit. Check with your institution to learn more.

  • You will be able to use R to create new data science tools as part of a team or a community of developers. You will be able to build R packages, develop custom visualizations, and apply modern software development tools to create reusable code for solving data science problems.

More questions? Visit the Learner Help Center.