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DavidsonX: RShiny for Everyone

Use R’s Shiny package to create data-driven, interactive web applications.

RShiny for Everyone
4 weeks
3–5 hours per week
Progress at your own speed
Optional upgrade available

There is one session available:

After a course session ends, it will be archivedOpens in a new tab.
Starts Dec 5

About this course

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In this hands-on course, you will learn how to use R Shiny to create data-driven web applications. By the end of the course, you will have created an interactive web application that highlights the biodiversity of America's National Parks. Your application will feature an interactive map, biodiversity calculator, trail journal and species images. Using R Shiny, you will expand your data analysis and visualization skills while developing a way to share and distribute your findings in an application. If you are a beginner level data professional, a student, a researcher, an academic marketing analyst, business and data analyst, or financial analyst, this course is for you.

This four week course will give you a foundation for making and deploying Shiny applications. Along the way you will learn about user interaction (UI) controls, persistent data storage using google sheets, customizing your application with CSS and publishing through You will create your own unique application(s) that you can share with friends, colleagues, and potential employers.

Course Requirement: Computer that can run R/RStudio - account (free) needed to deploy to the web.

At a glance

  • Language: English
  • Video Transcript: English
  • Associated skills: Market Research, Data Storage Technologies, RStudio, User Interface, Data Analysis, Shiny (R Package), R (Programming Language), Workflow Management, Financial Analysis, Cascading Style Sheets (CSS), Research, Web Applications, Google Sheets

What you'll learn

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  • Create data-driven applications to publish analytical findings
  • Visualize interactive bar charts, scatterplots, maps and images
  • Engage users through drop down menus and search inputs
  • Communicating to data sources using the Google Sheets API
  • Customize and style applications using Cascading Style Sheets (CSS)
  • In this RShiny tutorial, you'll gain training as we cover topics including R code, R script, Shiny server. These skills are applicable for data science, machine learning, working with open source code and working in github with datasets. Additional tangential skills include docker, docerize, tidyverse, shinymatrix, matrix inputs and more!

This course is meant to teach the basics of building an app using RShiny. It presents a general introduction to the capabilities of RShiny with a particular focus on "learning by doing." At the end of each week of instruction, you'll complete a "wrap-up exercise" and quiz that reinforce the techniques you've learned.

Week 1

  • Getting Set Up
  • Using R Studio IDE for Shiny
  • Basic UI
  • Client Side vs Server Side Components

Week 2

  • Server Side UI
  • Leaflet Maps
  • Server Side Outputs
  • Buttons, Modal Viewers and Observe Events

Week 3

  • Working with Data
  • The Reactive and Browser Functions
  • Customizing Your App with consideration of CSS Rules and Custom Skins
  • Deploying Your Application!

Week 4

  • Setting Things Up - Where to Begin
  • Starting a New Project
  • Filters for Interactivity
  • Maps and Journals
  • Final Projects!

Frequently Asked Questions

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I have never worked with RShiny or any programming language before. Should I take a beginner course prior to taking this course?

You've come to the right place. This course is built for beginners with limited experience with R and RStudio

What is the value of the verified track?

Beyond the certificate which you can post on LinkedIn and other social media channels to show off your accomplishment to others, you will also gain valuable supplementary matertials to dive deeper and take the next step beyond the audit track content to learn deeper within RShiny.

This course is part of Web App Development for Data Scientists Professional Certificate Program

Learn more 
Expert instruction
2 skill-building courses
Progress at your own speed
2 months
4 - 8 hours per week

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