Data visualization is a critical skill for anyone that routinely using quantitative data in his or her work - which is to say that data visualization is a tool that almost every worker needs today. One of the critical tools for data visualization today is the R statistical programming language. Especially in conjunction with the tidyverse software packages, R has become an extremely powerful and flexible platform for making figures, tables, and reproducible reports. However, R can be intimidating for first time users, and there are so many resources online that it can be difficult to sort through without guidance.
Getting Started with Data Visualization in R
Getting Started with Data Visualization in R
This course is part of Data Visualization & Dashboarding with R Specialization
Instructor: Collin Paschall
30,111 already enrolled
Included with 
Gain insight into a topic and learn the fundamentals.
4.7
(274 reviews)
Beginner level
No prior experience required
Flexible schedule
Approx. 11 hours
Learn at your own pace
95%
Most learners liked this course
Details to know
Shareable certificate
Add to your LinkedIn profile
Assessments
9 assignments
Taught in English
See how employees at top companies are mastering in-demand skills
Build your subject-matter expertise
This course is part of the Data Visualization & Dashboarding with 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
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 3 modules in this course
In this module, we will get set up with R to process data for visualizations. You should begin by watching the introductory videos in each lesson. Then, carefully review the readings and reference materials provided. Once you have done that, I recommend watching the videos again to check your understanding. You will take a few quizzes as you progress through the material to make sure you are keeping up.
What's included
8 videos7 readings4 assignments1 peer review
In this module, we will use functions from the tidyverse to manipulate data. You should begin by watching the introductory videos in each lesson. Then, carefully review the readings and reference materials provided. Once you have done that, I recommend watching the videos again to check your understanding. You will take a few quizzes as you progress through the material to make sure you are keeping up.
What's included
5 videos7 readings2 assignments1 peer review
In this module, we learn to make reproducible reports using R Markdown. You should begin by watching the introductory videos in each lesson. Then, carefully review the readings and reference materials provided. Once you have done that, I recommend watching the videos again to check your understanding. You will take a few quizzes as you progress through the material to make sure you are keeping up. Then, at the end of the module, you will submit an assignment for peer review that covers all of the material in this course.
What's included
3 videos8 readings3 assignments1 peer review
Instructor
Instructor ratings
4.7 (119 ratings)Offered by
Recommended if you're interested in Data Analysis
University of Michigan
Johns Hopkins University
Coursera Project Network
Why people choose Coursera for their career
Felipe M.
Learner since 2018
"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."
Jennifer J.
Learner since 2020
"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."
Larry W.
Learner since 2021
"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."
Chaitanya A.
"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."
Learner reviews
4.7
274 reviews
- 5 stars
83.21%
- 4 stars
12.40%
- 3 stars
2.18%
- 2 stars
0.36%
- 1 star
1.82%
Showing 3 of 274
EL
5
Reviewed on Jun 8, 2021
I very much appreciate Colin's style and pace. This course is really well done and I would recommend highly !
BS
5
Reviewed on Sep 26, 2021
An accessible introduction to the world of R and Ggplot. The Specialization is recommended for researchers of all areas.
OE
5
Reviewed on Dec 29, 2020
Great for learning data wrangling and visualization
New to Data Analysis? Start here.
Open new doors with Coursera Plus
Unlimited access to 10,000+ 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.