RShiny for Everyone
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 shinyapps.io. 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 - shinyapps.io account (free) needed to deploy to the web.
Upcoming start dates
- Self-paced Online
Who should attend?
Prior experience with R and RStudio is a plus.
- Getting Set Up
- Using R Studio IDE for Shiny
- Basic UI
- Client Side vs Server Side Components
- Server Side UI
- Leaflet Maps
- Server Side Outputs
- Buttons, Modal Viewers and Observe Events
- Working with Data
- The Reactive and Browser Functions
- Customizing Your App with consideration of CSS Rules and Custom Skins
- Deploying Your Application!
- Setting Things Up - Where to Begin
- Starting a New Project
- Filters for Interactivity
- Maps and Journals
- Final Projects!
Course delivery details
This course is offered through Davidson College, a partner institute of EdX.
3-5 hours per week
- Verified Track -$199
- Audit Track - Free
Certification / Credits
What you'll learn
- 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!
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