This course is part of the Data Visualization & Dashboarding with R Specialization

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Collin Paschall

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Data Visualization & Dashboarding with R SpecializationJohns Hopkins University

About this Course

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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.
To fill that need, this course is intended for learners who have little or no experience with R but who are looking for an introduction to this tool. By the end of this course, students will be able to import data into R, manipulate that data using tools from the popular tidyverse package, and make simple reports using R Markdown. The course is designed for students with good basic computing skills, but limited if any experience with programming.

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Course 1 of 5 in the

Data Visualization & Dashboarding with R Specialization

Beginner Level

Approx. 11 hours to complete

English

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Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Course 1 of 5 in the

Data Visualization & Dashboarding with R Specialization

Beginner Level

Approx. 11 hours to complete

English

Could your company benefit from training employees on in-demand skills?

Try Coursera for Business

Instructor

Instructor rating

4.68/5 (90 Ratings)

Collin Paschall

Senior Lecturer

Johns Hopkins University Center for Advanced Governmental Studies

17,536 Learners

5 Courses

Offered by

Johns Hopkins University

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Syllabus - What you will learn from this course

Week1

Week 1

4 hours to complete

Getting Started with Data Management and Visualization with R

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.

4 hours to complete

8 videos (Total 40 min), 7 readings, 5 quizzes

8 videos

Introduction to the Course2mIntroduction to R and Software Installation5mBasic R, Part 13mBasic R Part 25mFunctions in R3mDataframes7mBasics of Importing Data into R5mBase R Visualizations5m

7 readings

How to Watch the Videos2mThe RStudio Cheat Sheet20mBase R Cheat Sheet20mR for Data Science, Chapter 420mA Note on File Paths10mCCES Data5mCookbook for R: Basic Plots30m

4 practice exercises

Install R and Setup Quiz10mBase R and Functions Quiz10mDataframes and Importing Data in R10mBase R Visualization Quiz5m

Week2

Week 2

4 hours to complete

Using the Tidyverse packages

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.

4 hours to complete

5 videos (Total 27 min), 7 readings, 3 quizzes

5 videos

Introduction to the tidyverse5mData import and structure in the tidyverse4mFiltering, selecting, recoding, renaming, and piping5mRecoding, Renaming, and Calculating Columns6mGrouping and summarizing data4m

7 readings

R for Data Science, Introduction and Part II: Wrangle40mData Import Cheat Sheet10mtibble, readr, and tidyr Documentation30mR for Data Science, Chapter 530mData Wrangling Cheat Sheet10mGetting Started with dplyr20mLearning to Read R Documentation20m

2 practice exercises

Tidyverse Introduction Quiz15mManipulating Variables and Creating Summaries Quiz15m

Week3

Week 3

4 hours to complete

Using R Markdown to Make Reports

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.

4 hours to complete

3 videos (Total 15 min), 8 readings, 4 quizzes

3 videos

Creating reports with R Markdown6mR Markdown syntax and tables5mqplots and closing thoughts3m

8 readings

Note on Installing LaTex10mNote on Previewing Figures in R Markdown10mR for Data Science, Chapter 2710mR Markdown Cheat Sheet10mR Markdown Reference Guide10mR Markdown: The Definitive Guide10mqplot() Documentation20mA Note About Peer Review Assignments10m

3 practice exercises

R Markdown Intro Quiz10mR Markdown Syntax Quiz5mIncorporating Tables and Figures Quiz5m

Reviews

4.7

63 reviews

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1 star
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TOP REVIEWS FROM GETTING STARTED WITH DATA VISUALIZATION IN R

by AJDec 22, 2020

This is a great introductory course to R and data visualization in R.

by ATApr 11, 2021

I found this course interesting. It help me improve on the skills as a look to advance skills in R.

I liked the recode function. I had not yet used it

by AHDec 15, 2022

A clear. logical foundation for data cleaning and wrangling using the Tidyverse packages in R. an excellent introduction for beginners looking to begin their data science journey.

by RRMar 20, 2021

Good exercises and great format having peer-reviewed submissions.

Might have done visualizaiton in base R, first, but otherwise great intro.

View all reviews

About the Data Visualization & Dashboarding with R Specialization

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Getting Started with Data Visualization in R

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