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.
Ask the right questions, manipulate data sets, and create visualizations to communicate results. This Specialization covers the concepts and tools you'll need throughout the entire data science pipeline, from asking the right kinds of questions to making inferences and publishing results. In the final Capstone Project, you’ll apply the skills learned by building a data product using real-world data. At completion, students will have a portfolio demonstrating their mastery of the material.
In this overview module, we'll go over some information and resources to help you get started and succeed in the course.
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.
Graded: Quiz 1
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.
Graded: Quiz 2
Graded: R Markdown and Leaflet - 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.
Graded: Quiz 3
Graded: R Markdown Presentation & Plotly - Peer Review
Swirl and Course Project
Week 4 is all about the Course Project, producing a Shiny Application and reproducible pitch.
Graded: Course Project: Shiny Application and Reproducible Pitch - Peer Review