How do you update your causal inference skills?

1 Read books and papers

Gaining an understanding of the current state of the art in causal inference requires reading books and papers by experts in the field. Books can provide a comprehensive overview of the main concepts, frameworks, and techniques of causal inference, while papers can showcase the latest research findings, challenges, and innovations. To that end, some recommended books and papers include Causal Inference: What If by Miguel A. Hernán and James M. Robins, Causal Inference: The Mixtape by Scott Cunningham, The Book of Why: The New Science of Cause and Effect by Judea Pearl and Dana Mackenzie, A Crash Course in Good and Bad Controls by Paul R. Rosenbaum, and The Seven Tools of Causal Inference, with Reflections on Machine Learning by Jennifer Hill. These works cover topics such as the potential outcomes framework, causal graphs, econometric methods, causal diagrams, counterfactuals, and more.

2 Take online courses and workshops

To update your causal inference skills, you can take online courses and workshops that offer interactive and hands-on learning experiences, as well as feedback and guidance from instructors and peers. For example, Coursera offers a Causal Inference with R course that covers the basics of causal inference using R programming. Duke University provides a Causal Inference Bootcamp that teaches you how to design, analyze, and interpret causal inference studies using Python programming. Stanford University offers a Causal Inference for Data Science course that introduces advanced topics in causal inference using Python programming. And MITx has a Causal Inference for Social Science course that applies causal inference methods to social science questions using Stata programming.

3 Join online communities and events

If you want to improve your causal inference skills, joining online communities and events is a great way to do so. You can network, exchange ideas, ask questions, and learn from other enthusiasts and experts. Kaggle’s Causal Inference Community is a great place to start, as it hosts discussions, competitions, and datasets related to causal inference. Additionally, the Causal Inference Reading Group by Causal Inference UK organizes regular meetings to discuss books and papers on the topic. The American Statistical Association’s Causal Inference Conference is another great event for learning more about causal inference, featuring keynote speakers, panel sessions, tutorials, and posters. Finally, The Alan Turing Institute’s Causal Revolution event showcases the latest research and applications of causal inference in health, education, and social good.

4 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?