Build Shiny Apps Faster with AI

A practical, step-by-step guide to building dynamic dashboards, models, and workflows in R using AI support

What you’ll learn
Build interactive Shiny dashboards in R using a clear, step-by-step workflow without breaking existing functionality.
Use AI effectively to generate, extend, and debug Shiny apps while staying in full control of the code.
Create dynamic dashboards with filters, tabs, tables, and interactive Plotly visualizations.
Integrate logistic regression models into a Shiny app with user-selected predictors and real-time predictions.
Export results from dashboards by downloading model summaries and prediction outputs.
Design professional-looking dashboards using bslib themes without needing HTML or CSS.
Publish and share Shiny apps online using beginner-friendly deployment tools.

Requirements
Basic knowledge of R (you should be comfortable running scripts and working with data frames) R and RStudio installed on your computer No prior Shiny experience required No web development knowledge needed (HTML, CSS, or JavaScript are not required) No prior experience with AI tools required — everything is explained step by step If you’ve written R code before and want to build interactive dashboards faster and more confidently, you’re ready for this course.

Description
Building dashboards is easy — until you need flexibility.Many popular tools are excellent for creating static reports, but they quickly become limiting when your work requires dynamic logic, custom workflows, or integrated modeling. If you’ve ever found yourself re-running the same R scripts again and again just to test new scenarios, you already know the problem.This course shows you how to move beyond static dashboards and build dynamic, interactive Shiny applications that combine exploration, modeling, and automation — all in one place.Instead of teaching Shiny as a collection of isolated functions, this course focuses on how to think and work when building Shiny apps. You’ll learn a practical, step-by-step workflow that mirrors real projects: starting simple, extending safely, debugging intelligently, and turning analysis into reusable tools.A key part of this course is learning how to use AI as a development assistant, not a replacement. You’ll see how to write clear prompts, review AI-generated code, and stay fully in control of your application while dramatically speeding up development.Throughout the course, we build one complete analytics dashboard from start to finish. You’ll add filters, tabs, interactive tables, and Plotly visualizations. You’ll then integrate a logistic regression model where users can select predictors, generate predictions, run “what-if” scenarios, and download results — all without re-running scripts.You’ll also learn how to improve the look and usability of your app using modern layout tools, load data automatically, and publish your dashboard online so others can use it.This course is designed for people who already know some R and want to turn their analyses into interactive systems that save time, reduce repetition, and support real decision-making.If you want dashboards that don’t just show results — but actively help you work — this course is for you.

Who this course is for
Data analysts and data scientists who use R and want to build interactive dashboards instead of static reports. Researchers and academics who want to turn analyses and models into user-friendly tools without re-running scripts. Students with basic R knowledge who want practical, real-world dashboarding skills. Professionals working with data who feel limited by static tools like Power BI or Excel and need more flexibility.