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Johns Hopkins University
Developing Data Products
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  • Outcomes
  • Modules
  • Recommendations
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  1. Browse
  2. Data Science
  3. Data Analysis
Johns Hopkins University

Developing Data Products

This course is part of multiple programs.

This course is part of multiple programs

Data Science: Statistics and Machine Learning Specialization
Data Science Specialization
Brian Caffo, PhD
Jeff Leek, PhD
Roger D. Peng, PhD

Instructors: Brian Caffo, PhD

Instructors

Instructor ratings

We asked all learners to give feedback on our instructors based on the quality of their teaching style.

4.6 (70 ratings)
Brian Caffo, PhD
Brian Caffo, PhD
Johns Hopkins University
30 Courses•1,678,146 learners
Jeff Leek, PhD
Jeff Leek, PhD
Johns Hopkins University
32 Courses•1,712,758 learners
Roger D. Peng, PhD
Roger D. Peng, PhD
Johns Hopkins University
37 Courses•1,650,300 learners

86,332 already enrolled

Included with Coursera Plus

•Learn more
5 modules
Gain insight into a topic and learn the fundamentals.
4.6

(2,258 reviews)

1 week to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
94%
Most learners liked this course

5 modules
Gain insight into a topic and learn the fundamentals.
4.6

(2,258 reviews)

1 week to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
94%
Most learners liked this course
  • About
  • Outcomes
  • Modules
  • Recommendations
  • Testimonials
  • Reviews

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

  • Interactive Data Visualization
  • Hypertext Markup Language (HTML)
  • GitHub
  • Data Visualization Software
  • Plotly
  • User Interface (UI)
  • R Programming
  • Rmarkdown
  • Shiny (R Package)
  • Leaflet (Software)
  • Web Applications
  • Data Presentation
  • Statistical Reporting
  • Package and Software Management
  • Data Visualization

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

3 assignments

Taught in English

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Build your subject-matter expertise

This course is available as part of
When you enroll in this course, you'll also be asked to select a specific program.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 5 modules in this course

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.

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

1 video•Total 1 minute
  • Welcome to Developing Data Products•1 minute•Preview module
6 readings•Total 52 minutes
  • A Note of Explanation•2 minutes
  • Syllabus•10 minutes
  • Welcome•10 minutes
  • Book: Developing Data Products in R•10 minutes
  • Community Site•10 minutes
  • R and RStudio Links & Tutorials•10 minutes

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

24 videos•Total 123 minutes
  • Shiny 1.1•6 minutes•Preview module
  • Shiny 1.2•6 minutes
  • Shiny 1.3•4 minutes
  • Shiny 1.4•6 minutes
  • Shiny 1.5•9 minutes
  • Shiny 2.1•3 minutes
  • Shiny 2.2•9 minutes
  • Shiny 2.3•2 minutes
  • Shiny 2.4•4 minutes
  • Shiny 2.5•3 minutes
  • Shiny 2.6•6 minutes
  • Shiny Gadgets 1.1•5 minutes
  • Shiny Gadgets 1.2•4 minutes
  • Shiny Gadgets 1.3•7 minutes
  • GoogleVis 1.1•6 minutes
  • GoogleVis 1.2•8 minutes
  • Plotly 1.1•4 minutes
  • Plotly 1.2•2 minutes
  • Plotly 1.3•6 minutes
  • Plotly 1.4•5 minutes
  • Plotly 1.5•3 minutes
  • Plotly 1.6•4 minutes
  • Plotly 1.7•0 minutes
  • Plotly 1.8•1 minute
2 readings•Total 20 minutes
  • Shiny•10 minutes
  • Shinyapps.io Project•10 minutes
1 assignment•Total 10 minutes
  • Quiz 1•10 minutes

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

12 videos•Total 45 minutes
  • R Markdown 1.1•4 minutes•Preview module
  • R Markdown 1.2•2 minutes
  • R Markdown 1.3•3 minutes
  • R Markdown 1.4•0 minutes
  • R Markdown 1.5•3 minutes
  • R Markdown 1.6•6 minutes
  • Leaflet 1.1•3 minutes
  • Leaflet 1.2•5 minutes
  • Leaflet 1.3•2 minutes
  • Leaflet 1.4•2 minutes
  • Leaflet 1.5•2 minutes
  • Leaflet 1.6•6 minutes
1 reading•Total 10 minutes
  • Three Ways to Share R Markdown Products•10 minutes
1 assignment•Total 30 minutes
  • Quiz 2•30 minutes
1 peer review•Total 60 minutes
  • R Markdown and Leaflet•60 minutes

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

5 videos•Total 65 minutes
  • R Packages (Part 1)•7 minutes•Preview module
  • R Packages (Part 2)•14 minutes
  • Building R Packages Demo•18 minutes
  • R Classes and Methods (Part 1)•13 minutes
  • R Classes and Methods (Part 2)•11 minutes
1 reading•Total 10 minutes
  • R Packages•10 minutes
1 assignment•Total 30 minutes
  • Quiz 3•30 minutes
1 peer review•Total 60 minutes
  • R Markdown Presentation & Plotly•60 minutes

Week 4 is all about the Course Project, producing a Shiny Application and reproducible pitch.

What's included

3 videos1 reading1 peer review

3 videos•Total 16 minutes
  • Swirl 1.1•2 minutes•Preview module
  • Swirl 1.2•7 minutes
  • Swirl 1.3•6 minutes
1 reading•Total 10 minutes
  • Post-Course Survey•10 minutes
1 peer review•Total 60 minutes
  • Course Project: Shiny Application and Reproducible Pitch•60 minutes

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.

Instructors

Instructor ratings

Instructor ratings

We asked all learners to give feedback on our instructors based on the quality of their teaching style.

4.6 (70 ratings)
Brian Caffo, PhD
Brian Caffo, PhD
Johns Hopkins University
30 Courses•1,678,146 learners
Jeff Leek, PhD
Jeff Leek, PhD
Johns Hopkins University
32 Courses•1,712,758 learners

Instructors

Instructor ratings

We asked all learners to give feedback on our instructors based on the quality of their teaching style.

4.6 (70 ratings)
Brian Caffo, PhD
Brian Caffo, PhD
Johns Hopkins University
30 Courses•1,678,146 learners
Jeff Leek, PhD
Jeff Leek, PhD
Johns Hopkins University
32 Courses•1,712,758 learners
Roger D. Peng, PhD
Roger D. Peng, PhD
Johns Hopkins University
37 Courses•1,650,300 learners

Offered by

Johns Hopkins University

Offered by

Johns Hopkins University

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.

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Learner reviews

4.6

2,258 reviews

  • 5 stars

    68.42%

  • 4 stars

    23.16%

  • 3 stars

    6.42%

  • 2 stars

    1.50%

  • 1 star

    0.48%

Showing 3 of 2258

R
RB
5

Reviewed on Aug 28, 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

S
SK
5

Reviewed on Aug 1, 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.

J
JN
5

Reviewed on Sep 1, 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.

View more reviews
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