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Course Outline

Overview of Shiny

  • Definition of Shiny and its operational principles
  • Installation procedures and foundational setup
  • Review of Shiny examples and the gallery

UI and Server Structure

  • Analysis of ui.R and server.R components
  • Utilizing fluidPage(), sidebarLayout(), and other layout functions
  • Structuring inputs and outputs

Reactivity and Dynamic Behavior

  • Working with reactive expressions and observers
  • Regulating app logic through reactive inputs
  • Troubleshooting reactivity challenges

Data Visualization and Report Generation

  • Embedding ggplot2 and plotly within Shiny apps
  • Constructing reactive tables using DT or reactable
  • Producing downloadable reports via rmarkdown

Advanced UI Features and Customization

  • Implementing tabs, conditional panels, and modals
  • Applying custom CSS and themes
  • Leveraging Shiny modules for code modularity and reuse

Deployment and Hosting Strategies

  • Publishing apps to Posit Cloud or Shinyapps.io
  • Executing apps locally and via Shiny Server
  • Handling dependencies and version control

Practical Case Study and App Design

  • Developing a comprehensive dashboard from the ground up
  • Implementing interactive filters and user-driven analytical insights
  • Best practices for performance optimization, security, and scalability

Recap and Future Directions

Requirements

  • Solid grasp of R programming concepts
  • Practical experience in data analysis or visualization
  • Knowledge of HTML and CSS is advantageous, though not mandatory

Target Audience

  • Data analysts and scientists
  • R developers aiming to create interactive dashboards
  • Researchers and educators presenting data for public or internal consumption
 14 Hours

Number of participants


Price per participant

Open Training Courses require 5+ participants.

Testimonials (3)

a multitude of points

Joanna - Instytut Ekonomiki Rolnictwa i Gospodarki Zywnosciowej-PIB
Course - Statistical Analysis with Stata and R

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.

Matthew - Natural Resources Canada
Course - Data Analytics With R

Upcoming Courses

Shiny App Web Development with R

2026-10-19 09:30
14 hours
Mirobod
22,597,506 UZS (Online)
24,597,506 UZS (Classroom)

Shiny App Web Development with R

2026-11-02 09:30
14 hours
Mirobod
22,597,506 UZS (Online)
24,597,506 UZS (Classroom)

Shiny App Web Development with R

2026-11-16 09:30
14 hours
Mirobod
22,597,506 UZS (Online)
24,597,506 UZS (Classroom)

Shiny App Web Development with R

2026-11-30 09:30
14 hours
Mirobod
22,597,506 UZS (Online)
24,597,506 UZS (Classroom)

Shiny App Web Development with R

2026-12-14 09:30
14 hours
Mirobod
22,597,506 UZS (Online)
24,597,506 UZS (Classroom)

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