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Course Outline
Introduction to Shiny
- Overview of Shiny and its operational principles.
- Installation process and basic setup.
- Exploring Shiny examples and the official gallery.
UI and Server Architecture
- Understanding the roles of ui.R and server.R components.
- Utilizing fluidPage(), sidebarLayout(), and other layout functions.
- Designing effective inputs and outputs.
Reactivity and Dynamic Interactions
- Working with reactive expressions and observers.
- Controlling application behavior through reactive inputs.
- Identifying and resolving reactivity issues.
Data Visualization and Reporting
- Integrating ggplot2 and plotly into Shiny apps.
- Constructing reactive tables using DT or reactable.
- Generating downloadable reports via rmarkdown.
Advanced UI and Customization
- Implementing tabs, conditional panels, and modals.
- Incorporating custom CSS and themes.
- Utilizing Shiny modules for code reusability.
Deployment and Hosting
- Deploying applications to Posit Cloud or Shinyapps.io.
- Running applications locally and on Shiny Server.
- Managing dependencies and software versions.
Case Study and Application Design
- Building 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 in data analysis or visualization.
- Knowledge of HTML and CSS is beneficial but not mandatory.
Target Audience
- Data analysts and data scientists.
- R developers aiming 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.
