A data product is the production output from a statistical analysis. Data products automate complex analysis tasks or use technology to expand the utility of a data informed model, algorithm or inference. This course covers the basics of creating data products using Shiny, R packages, and interactive graphics. The course will focus on the statistical fundamentals of creating a data product that can be used to tell a story about data to a mass audience.
Johns Hopkins UniversityAbout this Course
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Learner Career Outcomes
30%
started a new career after completing these courses
34%
got a tangible career benefit from this course
14%
got a pay increase or promotion
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Approx. 10 hours to complete
English
Subtitles: English, Korean, Vietnamese
Skills you will gain
InteractivityPlotlyWeb ApplicationR Programming
Learner Career Outcomes
30%
started a new career after completing these courses
34%
got a tangible career benefit from this course
14%
got a pay increase or promotion
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Approx. 10 hours to complete
English
Subtitles: English, Korean, Vietnamese
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
1 hour to complete
Course Overview
In this overview module, we'll go over some information and resources to help you get started and succeed in the course.
1 hour to complete
1 video (Total 1 min), 6 readings
1 video
6 readings
A Note of Explanation2m
Syllabus10m
Welcome10m
Book: Developing Data Products in R10m
Community Site10m
R and RStudio Links & Tutorials10m
3 hours to complete
Shiny, GoogleVis, and Plotly
Now we can turn to the first substantive lessons. In this module, you'll learn how to develop basic applications and interactive graphics in shiny, compose interactive HTML graphics with GoogleVis, and prepare data visualizations with Plotly.
3 hours to complete
24 videos (Total 124 min), 2 readings, 1 quiz
24 videos
Shiny 1.26m
Shiny 1.34m
Shiny 1.46m
Shiny 1.59m
Shiny 2.13m
Shiny 2.29m
Shiny 2.32m
Shiny 2.44m
Shiny 2.53m
Shiny 2.66m
Shiny Gadgets 1.15m
Shiny Gadgets 1.24m
Shiny Gadgets 1.37m
GoogleVis 1.16m
GoogleVis 1.28m
Plotly 1.14m
Plotly 1.22m
Plotly 1.36m
Plotly 1.45m
Plotly 1.53m
Plotly 1.64m
Plotly 1.753s
Plotly 1.81m
2 readings
Shiny10m
Shinyapps.io Project10m
1 practice exercise
Quiz 130m
2 hours to complete
R Markdown and Leaflet
During this module, we'll learn how to create R Markdown files and embed R code in an Rmd. We'll also explore Leaflet and use it to create interactive annotated maps.
2 hours to complete
12 videos (Total 45 min), 1 reading, 2 quizzes
12 videos
R Markdown 1.22m
R Markdown 1.33m
R Markdown 1.459s
R Markdown 1.53m
R Markdown 1.66m
Leaflet 1.13m
Leaflet 1.25m
Leaflet 1.32m
Leaflet 1.42m
Leaflet 1.52m
Leaflet 1.66m
1 reading
Three Ways to Share R Markdown Products10m
1 practice exercise
Quiz 230m
3 hours to complete
R Packages
In this module, we'll dive into the world of creating R packages and practice developing an R Markdown presentation that includes a data visualization built using Plotly.
3 hours to complete
5 videos (Total 65 min), 1 reading, 2 quizzes
5 videos
R Packages (Part 2)14m
Building R Packages Demo18m
R Classes and Methods (Part 1)13m
R Classes and Methods (Part 2)11m
1 reading
R Packages10m
1 practice exercise
Quiz 330m
1 hour to complete
Swirl and Course Project
Week 4 is all about the Course Project, producing a Shiny Application and reproducible pitch.
1 hour to complete
3 videos (Total 16 min), 1 reading, 1 quiz
1 reading
Post-Course Survey10m
Reviews
TOP REVIEWS FROM DEVELOPING DATA PRODUCTS
by VPApr 9, 2017
Nice course and good classmates. It's very focus oriented and gives very good idea of Shiny, Rmarkdown, plotly and how to publish documents on github, Rpubs and other online sites. I learnt power of R
by JCMay 4, 2016
Compared to the other classes in the JHU Data Science specialization, this one is pretty laid back. It's useful information, and teaches a few nice tricks on how to present data analysis results.
by SRFeb 13, 2018
This course lacked required information of help to get started. Now thanks to some posts by mentors i was able to successfully complete the Capstone project. Overall a very good experience!
by SSMar 3, 2016
This is a great introduction to some of the many ways to present your data. It's probably the easiest course in the specialisation but shows off an impressive array of widgets and gadgets.
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- 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.
Will I earn university credit for completing the Course?
This Course doesn't carry university credit, but some universities may choose to accept Course Certificates for credit. Check with your institution to learn more. Online Degrees and Mastertrack™ Certificates on Coursera provide the opportunity to earn university credit.
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