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.
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About this Course
최근 조회 47,317회
배울 내용
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
귀하가 습득할 기술
InteractivityPlotlyWeb ApplicationR Programming
Course을(를) 수강하는 학습자
- Data Scientists
- Data Analysts
- Risk Managers
- Biologists
- Business Analysts
강의 계획 - 이 강좌에서 배울 내용
주
1완료하는 데 1시간 필요
Course Overview
In this overview module, we'll go over some information and resources to help you get started and succeed in the course.
1개 동영상 (총 1분), 5 readings
1개의 동영상
5개의 읽기 자료
Syllabus10m
Welcome10m
Book: Developing Data Products in R10m
Community Site10m
R and RStudio Links & Tutorials10m
완료하는 데 3시간 필요
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.
24개 동영상 (총 124분), 2 readings, 1 quiz
24개의 동영상
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 1.753
Plotly 1.81m
2개의 읽기 자료
Shiny10m
Shinyapps.io Project10m
1개 연습문제
Quiz 110m
주
2완료하는 데 3시간 필요
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.
12개 동영상 (총 45분), 1 reading, 2 quizzes
12개의 동영상
R Markdown 1.22m
R Markdown 1.33m
R Markdown 1.459
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
1개의 읽기 자료
Three Ways to Share R Markdown Products10m
1개 연습문제
Quiz 212m
주
3완료하는 데 3시간 필요
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.
5개 동영상 (총 65분), 1 reading, 2 quizzes
5개의 동영상
R Packages (Part 2)14m
Building R Packages Demo18m
R Classes and Methods (Part 1)13m
R Classes and Methods (Part 2)11m
1개의 읽기 자료
R Packages10m
1개 연습문제
Quiz 38m
주
4완료하는 데 2시간 필요
Swirl and Course Project
Week 4 is all about the Course Project, producing a Shiny Application and reproducible pitch.
3개 동영상 (총 16분), 1 reading, 1 quiz
1개의 읽기 자료
Post-Course Survey10m
4.6
344개의 리뷰30%
이 강좌를 수료한 후 새로운 경력 시작하기
33%
이 강좌를 통해 확실한 경력상 이점 얻기
14%
급여 인상 또는 승진하기
Developing Data Products의 최상위 리뷰
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.
This course was amazing, it could definetly be more deep in each of the subjects, but gives you so much practice in tools that are very useful in the day by day of a data scientist
강사
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
존스홉킨스대학교 정보
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.
데이터 과학 전문 분야 정보
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.
자주 묻는 질문
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