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

Collin Paschall

Offered By

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.
This is the final course in the Specialization "Data Visualization and Dashboarding in R." Learners in this course will enter with a well-developed set of skills making a wide variety of visualizations in R. The focus on this course will applying those skills to a unique project, drawing on publicly available data to tell a compelling story using the data visualization toolkit assembled in the previous courses.

Shareable Certificate

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Course 5 of 5 in the

Data Visualization & Dashboarding with R Specialization

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Approx. 22 hours to complete

English

Subtitles: English

Instructor

Collin Paschall

Senior Lecturer

Johns Hopkins University Center for Advanced Governmental Studies

2,337 Learners

5 Courses

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Course 5 of 5 in the

Data Visualization & Dashboarding with R Specialization

Flexible deadlines

Reset deadlines in accordance to your schedule.

Approx. 22 hours to complete

English

Subtitles: English

Offered by

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.

Syllabus - What you will learn from this course

Week

Week 1

6 hours to complete

Developing Your Eye and Finding Data

In this module, we will review the requirements for the capstone project and some possible souces for data. Then, we have a very fast overview of resources on good data visualization practice.

6 hours to complete

6 videos (Total 24 min), 10 readings, 2 quizzes

6 videos

Welcome to the Course and Project Overview2m

Project Overview and Tips for Locating Data5m

Data Import2m

Data Viz Pointers6m

Anscombe's Quartet and DatasauRus2m

More Best Practices and Readings Overview5m

10 readings

Many Data Sources10m

R for Data Science, Data Import10m

Data Import Cheat Sheet10m

R Graph Gallery10m

UC Berkeley Data Viz Guide10m

Duke University, Data Viz Guide10m

Healy, Chapter 110m

Clause Wilke text, Chapters 4 and 510m

EEA Guide10m

Junk Charts10m

Week

Week 2

6 hours to complete

Cleaning Your Data

In this module, we will review the requirements for the second component of your capstone project, where you will demonstrate that your data is ready for visualization. Then, we (re)introduce some important tools for cleaning data in R.

6 hours to complete

5 videos (Total 19 min), 11 readings, 5 quizzes

5 videos

Week 2 Overview2m

Strings4m

Lubridate2m

Factors2m

Joins and Pivots6m

11 readings

stringr Cheat Sheet10m

Getting Started with stringr10m

R for Data Science, Strings10m

Peng, R Programming for Data Science, Regular Expressions10m

R for Data Science, Ch. 1610m

Lubridate Cheat Sheet10m

Lubridate Reference, Intro10m

R for Data Science, Factors10m

Introduction to forcats10m

Relational Data10m

R for Data Science, Tidy Data10m

4 practice exercises

stringr quiz5m

lubridate quiz5m

forcats quiz5m

Tidying Data Quiz5m

Week

Week 3

9 hours to complete

Making Your Report

In this module, you will do one more visualization critique, and the rest of your time in the week should be devoted to finishing your capstone project.

9 hours to complete

About the Data Visualization & Dashboarding with R Specialization

This Specialization is intended for learners seeking to develop the ability to visualize data using R. Through five courses, you will use R to create static and interactive data visualizations and publish them on the web, which will you prepare you to provide insight to many types of audiences.

Frequently Asked Questions

When will I have access to the lectures and assignments?
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.
What will I get if I subscribe to this Specialization?
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.
Is financial aid available?
Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.

More questions? Visit the Learner Help Center.

Data Visualization Capstone