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Course Outline
Introduction to Shiny
- Understanding what Shiny is and its functionality.
- Installation and basic setup.
- Exploring Shiny examples and the gallery.
UI and Server Architecture
- Understanding the ui.R and server.R components.
- Working with fluidPage(), sidebarLayout(), and other layout functions.
- Designing inputs and outputs.
Reactivity and Dynamic Interactions
- Reactive expressions and observers.
- Controlling app behaviour through reactive inputs.
- Debugging reactivity issues.
Data Visualization and Reporting
- Integrating ggplot2 and plotly within Shiny apps.
- Building 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.
- Using 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
- Building a full-featured dashboard from scratch.
- Interactive filters and user-driven insights.
- Tips for performance, security, and scalability.
Summary and Next Steps
Requirements
- A foundational understanding of R programming.
- Experience in data analysis or visualization.
- Familiarity with HTML and CSS is beneficial but not mandatory.
Audience
- Data analysts and scientists.
- R developers aiming to build interactive dashboards.
- Researchers and educators visualizing data for public or internal purposes.
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.
