Dashboards and web apps

Learn how to create compelling dashboards and how to publish, share and secure them. The course discusses the pros and cons of various technologies and provides in-depth experience of developing web applications in the R framework Shiny.

Course syllabus

  • There are many ways to develop dashboards. We will learn about the various technological approaches to creating data focused web applications and explain the potential sweetspot of the R Shiny web framework
  • You will learn about the basic concepts of framework in a practical, hands-on session in which we develop a small but useful Shiny app
  • The R community has created many packages for Shiny. We talk about themes, widgets, charts, maps and tables.
  • For more complex apps we explain how code can be effectively organized into separate Shiny modules
  • Using the package manager packrat makes Shiny apps portable facilitating collaborative development and straightforward deployment into production
  • Shiny apps should feel quick and responsive. We share our experiences with data backends and their integration into the app.
  • Finally, we discuss how to deploy a Shiny app into production in a secure enterprise context. We cover the existing options and talk about deployment automation.

Course prerequisites

The course is aimed at business and data analysts who already have some experience with R, confidently use functions and know R’s basic data structures (lists, vectors, data frames). Previous knowledge of web technologies like HTML, CSS and JavaScript is beneficial but not required.

What should you bring?

You should bring a laptop to participate the practical part of the course. After registration we will provide you with links to download all course materials and relevant software to install.

Instructor — Stefan Schliebs, PhD

Stefan is the lead data scientist at Quantiful. He holds a Master degree in Computer Science from the University of Leipzig, Germany and a PhD from the Auckland University of Technology. He received numerous academic rewards, published more than 35 scientific articles in international journals, conferences and books and lectured data science courses on university level to 100s of students. He worked as a data scientist in various industries and has 10+ years of experience in commercial and academic environments. He is a co-organizer of the R User Meetup Group Auckland and Hackathon participant.


Details will be announced closer to the course date.

Course fees


There are limited seats at a discounted price for early career professionals and graduates.


Please leave us your email address and we will get back to you with more details shortly.