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Course Outline
Introduction to Shiny
- What is Shiny and how it works
- Installation and basic setup
- Exploring Shiny examples and gallery
UI and Server Architecture
- Understanding ui.R and server.R components
- Working with fluidPage(), sidebarLayout(), and layout functions
- Designing inputs and outputs
Reactivity and Dynamic Interactions
- Reactive expressions and observers
- Controlling app behavior with reactive inputs
- Debugging reactivity issues
Data Visualization and Reporting
- Integrating ggplot2 and plotly in Shiny apps
- Building reactive tables with DT or reactable
- Generating downloadable reports with rmarkdown
Advanced UI and Customization
- Adding tabs, conditional panels, and modals
- Incorporating custom CSS and themes
- Using Shiny modules for code reuse
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
- Building a full-featured dashboard from scratch
- Interactive filters and user-driven insights
- Tips for performance, security, and scalability
Summary and Next Steps
Requirements
- An understanding of R programming
- Experience working with data analysis or visualization
- Familiarity with HTML and CSS is helpful but not required
Audience
- Data analysts and scientists
- R developers seeking to build interactive dashboards
- Researchers and educators visualizing data for public or internal use
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.
