Description

Introduction

“Mastering Shiny: Advanced App Development in R” is designed for R developers ready to take their Shiny skills to the next level. This course dives into scalable architecture, modular design, performance optimization, and production deployment. It enables you to create robust, interactive web applications tailored for enterprise and data-intensive environments.

Prerequisites

• Proficient in R programming

• Prior experience with Shiny basics (UI/server structure, inputs/outputs, reactivity)

• Familiarity with ggplot2, dplyr, and data manipulation in R

• Basic knowledge of web technologies (HTML/CSS) is helpful

Table of Contents

1. Advanced Reactivity Techniques
1.1 Reactive Graph Deep Dive
1.2 Using isolate(), req(), invalidateLater()
1.3 Scoped Reactivity and Reactive Programming Pitfalls
1.4 Debugging with reactlog and browser()

2. Modular Application Architecture
2.1 Creating and Using Shiny Modules
2.2 Namespacing and Module Communication
2.3 Structuring Complex Projects
2.4 Building Reusable Components

3. Enhanced UI and UX Design
3.1 Dynamic UI with renderUI() and Conditional Panels
3.2 Responsive Layouts with bslib and shiny.semantic
3.3 Advanced Input Controls with shinyWidgets and shiny.fluent
3.4 Custom Styling with CSS and Theming

4. Database and API Integration
4.1 Connecting to Relational Databases using DBI
4.2 Using REST APIs with httr and jsonlite
4.3 Real-Time Data Feeds and Caching
4.4 Secure Credential Management

5. Performance Optimization
5.1 Profiling and Bottleneck Detection
5.2 Caching and Memoization Strategies
5.3 Efficient Data Rendering with DT and plotly
5.4 Throttling, Debouncing, and Load Handling

6. Testing and Quality Assurance
6.1 Unit Testing with testthat
6.2 UI Testing with shinytest2
6.3 Error Handling and Logging
6.4 Maintaining Code Quality and Version Control

7. Deployment and DevOps
7.1 Deploying with Shiny Server and RStudio Connect
7.2 Dockerizing Shiny Apps
7.3 CI/CD with GitHub Actions
7.4 Monitoring and Auto-Restart Mechanisms

8. Security and Authentication
8.1 Role-Based Access Control with shinymanager
8.2 Using OAuth2 and External Identity Providers
8.3 Secure Data Handling and App Hardening
8.4 Session Management and Timeout Policies

9. Building for Enterprise
9.1 Designing Scalable Shiny Architectures
9.2 App Maintenance and Lifecycle Strategy
9.3 Integrating Shiny with Data Science Pipelines
9.4 Supporting Multi-User Environments

10. Case Studies and Hands-On Projects
10.1 Real-Time Data Dashboard
10.2 Interactive Reporting Platform with Export Options
10.3 Shiny Front-End for Predictive Models
10.4 End-to-End Application Review

By the end of this course, you’ll have the tools to build, scale, and maintain advanced Shiny applications with confidence. You’ll master modular design, optimize performance, secure your apps, and deploy for real-world impact—elevating your R development career and your organization’s data capabilities.