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.
Developing Data Products
Developing Data Products
This course is part of multiple programs.
Instructors: Brian Caffo, PhD
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4.6
(2,256 reviews)
10 hours to complete
3 weeks at 3 hours a week
Flexible schedule
Learn at your own pace
94%
Most learners liked this course
What you'll learn
Develop basic applications and interactive graphics using GoogleVis
Use Leaflet to create interactive annotated maps
Build an R Markdown presentation that includes a data visualization
Create a data product that tells a story to a mass audience
Skills you'll gain
Details to know
Shareable certificate
Add to your LinkedIn profile
Assessments
3 assignments
Taught in English
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There are 5 modules in this course
In this overview module, we'll go over some information and resources to help you get started and succeed in the course.
What's included
1 video6 readings
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.
What's included
24 videos2 readings1 assignment
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.
What's included
12 videos1 reading1 assignment1 peer review
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.
What's included
5 videos1 reading1 assignment1 peer review
Week 4 is all about the Course Project, producing a Shiny Application and reproducible pitch.
What's included
3 videos1 reading1 peer review
Instructors
Instructor ratings
4.6 (70 ratings)Offered by
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University of Maryland, College Park
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4.6
2,256 reviews
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Showing 3 of 2256
RB
5
Reviewed on Aug 27, 2019
It is a very good course. There's quite some work, but the content isn't hard. Make sure you update your RStudio for all the features to work correctly
SK
5
Reviewed on Jul 31, 2019
It is a good course provide neccessary stuffs for data science.You can skip week 4 as it is done previously in other courses . Small and good course.
JN
5
Reviewed on Aug 31, 2017
Brian Caffo is the best! No one could explain better than him. Congratulations for this excellent course, you are my inspiration to become a better data scientist.
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Frequently asked questions
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