Teaching Resources

SOC 121D People Analytics: Data and Algorithms and Managerial Tools

Can machine learning help businesses hire (or fire) the right people? Can data science be used to close the gender pay gap? In this class, we'll explore the promises and pitfalls of using contemporary data analytics to help organizations manage their human resources. In doing so, we'll carefully examine the cutting-edge tools used by people analysts, use formal perspectives of human organization to think through the possible consequences of implementing these solutions in a business, and reason critically about the societal and ethical implications of their proliferation. No background in data science, computer science, or advanced mathematics is assumed for this class.

All course materials are available at my Github.

SICSS Festival 2021

In the summer of 2021 I was invited to present at the Summer Institute in the Social Sciences (SICSS) Summer Festival, an opportunity for SICSS alum to share their knowledge of computational methods with the world. I elected to hold a workshop titled "Introduction to Text Analysis in Python: A Hands-on Tutorial". It was an ambitious workshop, but I split the material between the hour-long live session and an extensively documented Google Colab notebook. Find the link to the video here and the Google Colab notebook here.

SOC 382 Teaching Material

While a teaching assistant for Professor Michael Rosenfeld's SOC 382 (Principles of Regression Analysis), I was given the opportunity to give my own series of lectures at the end of the quarter. I decided to give students a brief introduction to causal inference and machine learning, using the final lecture to probe and solidify the epistemological foundations of prediction and explanation, and how we can leverage one to better inform the other. Find the materials for these lectures here.

SICSS 2019 Flash Talk

During the 2019 Princeton SICSS, participants such as myself were able to give "flash talks" on methods or topics to the other participants. I gave a short talk on analyzing networks against null models, via simulation. The accompanying code demo is available on my GitHub page.