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.
课程信息
4.5
1,628 个评分
您将学到的内容有
Build an R Markdown presentation that includes a data visualization
Create a data product that tells a story to a mass audience
Develop basic applications and interactive graphics using GoogleVis
Use Leaflet to create interactive annotated maps
您将获得的技能
InteractivityPlotlyWeb ApplicationR Programming
教学大纲 - 您将从这门课程中学到什么
周
1完成时间为 1 小时
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 个视频 （总计 1 分钟）, 5 个阅读材料
5 个阅读材料
Syllabus10分钟
Welcome10分钟
Book: Developing Data Products in R10分钟
Community Site10分钟
R and RStudio Links & Tutorials10分钟
完成时间为 3 小时
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.
24 个视频 （总计 124 分钟）, 2 个阅读材料, 1 个测验
24 个视频
Shiny 1.16分钟
Shiny 1.26分钟
Shiny 1.34分钟
Shiny 1.46分钟
Shiny 1.59分钟
Shiny 2.13分钟
Shiny 2.29分钟
Shiny 2.32分钟
Shiny 2.44分钟
Shiny 2.53分钟
Shiny 2.66分钟
Shiny Gadgets 1.15分钟
Shiny Gadgets 1.24分钟
Shiny Gadgets 1.37分钟
GoogleVis 1.16分钟
GoogleVis 1.28分钟
Plotly 1.14分钟
Plotly 1.22分钟
Plotly 1.36分钟
Plotly 1.45分钟
Plotly 1.53分钟
Plotly 1.64分钟
Plotly 1.753
Plotly 1.81分钟
2 个阅读材料
Shiny10分钟
Shinyapps.io Project10分钟
1 个练习
Quiz 110分钟
周
2完成时间为 3 小时
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.
12 个视频 （总计 45 分钟）, 1 个阅读材料, 2 个测验
12 个视频
R Markdown 1.22分钟
R Markdown 1.33分钟
R Markdown 1.459
R Markdown 1.53分钟
R Markdown 1.66分钟
Leaflet 1.13分钟
Leaflet 1.25分钟
Leaflet 1.32分钟
Leaflet 1.42分钟
Leaflet 1.52分钟
Leaflet 1.66分钟
1 个阅读材料
Three Ways to Share R Markdown Products10分钟
1 个练习
Quiz 212分钟
周
3完成时间为 3 小时
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.
5 个视频 （总计 65 分钟）, 1 个阅读材料, 2 个测验
5 个视频
R Packages (Part 2)14分钟
Building R Packages Demo18分钟
R Classes and Methods (Part 1)13分钟
R Classes and Methods (Part 2)11分钟
1 个阅读材料
R Packages10分钟
1 个练习
Quiz 38分钟
周
4完成时间为 2 小时
Swirl and Course Project
Week 4 is all about the Course Project, producing a Shiny Application and reproducible pitch.
3 个视频 （总计 16 分钟）, 1 个阅读材料, 1 个测验
1 个阅读材料
Post-Course Survey10分钟
4.5
320 个审阅29%
完成这些课程后已开始新的职业生涯
34%
通过此课程获得实实在在的工作福利
16%
加薪或升职
热门审阅
创建者 SS•Mar 4th 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.
创建者 JR•Feb 5th 2017
A course where you can show everything learned in the R language, especially in visualizations.\n\nI hope and in the future there are courses focused only on visualization with R
讲师
Brian Caffo, PhD
Professor, BiostatisticsBloomberg School of Public Health
Jeff Leek, PhD
Associate Professor, BiostatisticsBloomberg School of Public Health
Roger D. Peng, PhD
Associate Professor, BiostatisticsBloomberg School of Public Health
关于 约翰霍普金斯大学
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.
关于 数据科学 专项课程
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.
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