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Course Outline
Introduction to Shiny
- Understanding Shiny and its mechanics
- Installation and initial setup
- Exploring Shiny examples and gallery
UI and Server Architecture
- Grasping ui.R and server.R components
- Utilizing fluidPage(), sidebarLayout(), and other layout functions
- Designing inputs and outputs
Reactivity and Dynamic Interactions
- Working with reactive expressions and observers
- Controlling app behavior through reactive inputs
- Troubleshooting reactivity issues
Data Visualization and Reporting
- Integrating ggplot2 and plotly within Shiny apps
- Constructing reactive tables using DT or reactable
- Generating downloadable reports with rmarkdown
Advanced UI and Customization
- Adding tabs, conditional panels, and modals
- Incorporating custom CSS and themes
- Utilizing Shiny modules for code reusability
Deployment and Hosting
- Deploying apps to Posit Cloud or Shinyapps.io
- Running apps locally and on Shiny Server
- Managing dependencies and versions
Case Study and Application Design
- Developing a comprehensive dashboard from scratch
- Implementing interactive filters and user-driven insights
- Best practices for performance, security, and scalability
Summary and Next Steps
Requirements
- Familiarity with R programming
- Experience with data analysis or visualization
- Basic knowledge of HTML and CSS is beneficial but not mandatory
Target Audience
- Data analysts and scientists
- R developers looking to build interactive dashboards
- Researchers and educators visualizing data for internal or public consumption
14 Hours
Testimonials (2)
knowledge of the trainer, tailor based, all topics covered
eleni - EUAA
Course - Forecasting with R
The real life applications using Statcan and CER as examples.