Teaching Causality and Causal ML with Shiny Apps

Dear R Users, we are happy to announce our next Meetup! This time it's about how R's popular framework for creating almost arbitrarily complex web applications, R-Shiny, can be leveraged to entice students to delve into data analysis/visualization and causal inference/ML within a University setting!

Besides that, as always, there will be the opportunity for a pleasant chat over a cold drink and a slice of pizza 🍕🍕🍕

Agenda
18:30 Open Door
18:50 Welcome & AOB
19:00 Teaching Causality and Causal ML with Shiny - Gangli Tan & Philipp Bach
19:45 Break
20:00 Meet the Speakers
20:30 Chill out and drinks

R Shiny Apps for Teaching Causality and Causal ML
Shiny apps offer students the opportunity to interact with data and complex statistical topics without prior knowledge of coding. Students get curious about how to generate data visualizations, perform statistical analyses or develop their own apps. Our speakers Gangli and Philipp are going to share examples and experiences from teaching causal inference with shiny apps. The Digital Causality Lab (DCL) is an innovative teaching project at the University of Hamburg which focuses on the topics Causal Inference and Data Literacy. Shiny apps are an integral part of the DCL teaching materials - both as teaching devices but also as examples for student projects. A brief introduction to causality as well as an outlook to Causal Machine Learning will be part of the talk, too. Gangli and Philipp are very happy to present their project to Hamburg R Users, to get some feedback and ideas for more apps in the future!

About the Speakers
Philipp Bach is a post-doctoral researcher at the Chair of Statistics with Application in Business Administration at the University of Hamburg. His research focuses on software implementations and empirical applications of causal machine learning approaches, most importantly double/debiased machine learning in R and Python. Philipp does not only enjoy teaching to students but also to data scientists from industry, mostly in the context of causal machine learning.

Gangli Tan is a research assistant and PhD candidate at the University of Hamburg. She just completed a M.Sc. degree in Business Administration, majoring in Management and Marketing. She is highly interested in causal machine learning, managing AI and digital innovation and transformation in organizations. Gangli has been part of the Digital Causality Lab from the very first day and has contributed to the shiny apps and the teaching materials.