Courses
I teach methodologically focused courses using either R or Python (both have their advantages!).
Quantitative
I teach our math camp to incoming first-year MACSS students and to any students interested in our certificate and/or strengthening their background in quantitative methods. It’s a fast-paced course. The github repo is available here and I built the course off materials from Benjamin Soltoff and Justin Grimmer, among others.
Python-Based
I teach two courses primarily based in Python: an intro to programming course and an ABM course. I am also developing a course on computational approaches to music from the perspective of the social sciences.
Intro to Python
This is a course aimed at students new to programming. The Python course has been built and contributed to by many people, especially including Ann Rogers, Borja Sotomayor, and Zhao Wang. I continue to develop and interate on the material and the course materials are available here on github. (Note: for this course, I use Canvas, so the repo is not particularly tidy!)
ABM: Agent-based Modeling
This course is taught in Python using the Mesa library. It incorporates a blend of seminar-style readings and hands-on applications using canonical models in ABM.
For more information, see the course repo on github.
R-based
I teach two course that are primarily based in R: Computing for the Social Sciences and Data Vizualization.
Data viz
Data Visualization is a very fun course and covers not only the fundamentals of visualization (primarily in R) but works on three important elements: Tableau, Shiny, and creating a website. Below you can see two examples from the course in their relative platforms. The data visualization course materials are available here.