Build a real time COVID-19 web dashboard in R

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Build and deploy a real-time analytics dashboard (optionally with your custom sub-domain, for free) with this multi-part lesson. The course will walk you through the process of cleaning data, creating highly compelling data visualizations, and then combining them with a web app framework that is pleasant and visually appealing.

By the end of this course, you will have a web dashboard that is deployed and accessible on the web by anyone, on any devices (responsive web design).

Learning Outcomes

  • Learn to develop a modern, reactive web application using R and the Shiny Web App framework
  • Learn to use one of the most popular, powerful data visualization library (ggplot) to create compelling visuals on the web
  • Learn to take advantage of modern web development practices such as Bootstrap 4, responsive web design, and UX thinking
  • Learn how a framework like Shiny allows you to author your application by transforming your R code into HTML, CSS and JavaScript
  • Learn to deploy your own Shiny web application with custom assets (images, scripts, logos). Sample: COVID-19 Web Application in R and Shiny

Sample Screenshots of Project Outcomes

One-time purchase. 10 Lessons and a launched project.

  • One time purchase and you unlock the full content of the course, forever.
  • Periodically updated to stay compatible with major releases of R and all major R packages used in the project.
  • The final product is yours to keep, to deploy, to monetize, to remix, modify and distribute (in fact, I encourage you to make money out of your mini-projects!)
  • 10 Lessons worth 30 hours of full-length project-driven tutorial. For a launch price of $29.90. That’s $2.99 per full lesson, or $1 per hour, or $29.90 for a a lifetime of knowledge
  • I will support you, for as long as it takes for you to complete the course. My average response time is measured in minutes, not days.

Data Visualization in R and ggplot2

Starting Point: Data Visualization

An introduction to plotting in R, and how data scientists can benefit from a rich “grammar” for data visualization.

Data Visualization in R and ggplot2
Cleaning data with dplyr

Data Preprocessing in R

A series of techniques for practical data manipulation, data cleansing, and data transformation in R (collectively called “data preprocessing”)

Cleaning data with dplyr
Web Application Anatomy with Shiny

Web Dashboards and Applications in R

Learn the design principles behind Shiny, a popular web app framework among R developers and data scientists

Web Application Anatomy with Shiny
Building Shiny Web Apps

Build and Deploy your Web Application

Take your web dashboard “Live” after adding some CSS and JavaScript polish, courtesy of external libraries that integrate well with Shiny

Building Shiny Web Apps


  • Some familiarity in R programming and working with RStudio IDE

Estimated Time

  • Lessons: 20-30 Hours (2-3 hours per programming lesson; 10 lesson in total)
  • Deployment and Server Administration: 2 Hours


Will I be able to follow along the course with no programming experience in R?

Install RStudio following the instruction on Installing and Configuring RStudio lesson (free) and take at least the Dive Deeper into RStudio lesson (free); The two lessons will walk you through the basics of working with R. Once you have completed the exercises in those two lessons, proceed to this course.

Will I need to buy a domain name or a hosting service to host my web app?

A free sub-domain and a free hosting service will be provided to you, courtesy of
You do not need to spend anything on domain name and hosting service to get your app up and running, ready for the world to see. At some point in the future, when you’re more ready financially, you can invest the time and money to have this hosted on your own, at your own domain name ( I have a course planned for that.

What is the end product we will be building?

Throughout the series we will be building not just one, but six variants of the app, starting from a bare-minimum (minimally viable product) app to a full fledged, interactive, real-time web analytics that is hosted online (think: You will be given the code skeleton, code references, image assets and written instructions to develop your app, but also encouraged to explore different styles and creative decisions. Your end product hence may be different depending on how you approach the allowable margin of creativity, but is expected to be heavily guided to a defined outcome:

How about continuity support?

I periodically update all my course materials (as you can see from my GitHub activity / logs), so they continue to work with the latest version of the programming language as well as other dependencies. When you enroll, you will receive a greeting and “thank you” email from me – to which you can reply to anytime you have technical questions relating to the course. Expect a response in 6 hours, usually much shorter than that.
I am highly committed to answering questions, and helping you in your learning journey.

Is this a recurring payment or a one-off payment? Does the course expire?

This course, as well as all future courses on Fine Tutorials, will never expire. You will always be able to access the full content once its unlocked. It’s a one-time payment, and lifetime access.

Downloadable Materials

Download the code materials, workbooks, and code required to follow the first few lessons:

  1. Cleaned CSV from my GitHub account
  2. Workbook: Complete learnPlotting.Rmd 
  3. Workbook: Complete plottingBasics.Rmd
  4. Workbook: Complete learnggplot.Rmd 
  5. Workbook: Complete learndplyr.Rmd
  6. Assets: Logo, image assets for your web application in RTapp/www folder 
  7. For Lesson 7-10, all code templates and scripts are in the RTapp folder

Course Content

Starting our Project
Data Visualization in R
Data Cleansing and Transformation in R
Web Application Development in R