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.
제공자:
이 강좌에 대하여
학습자 경력 결과
30%
34%
14%
배울 내용
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
귀하가 습득할 기술
학습자 경력 결과
30%
34%
14%
제공자:

존스홉킨스대학교
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.
강의 계획 - 이 강좌에서 배울 내용
Course Overview
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.
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.
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.
Swirl and Course Project
Week 4 is all about the Course Project, producing a Shiny Application and reproducible pitch.
검토
DEVELOPING DATA PRODUCTS의 최상위 리뷰
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
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.
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!
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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