Research in International Politics. Spring 2017. University of Texas at Austin. Syllabus.

Course Description: This course is the second semester of a capstone course in social science research that focuses on emerging questions in International Relations. In this class, students learn how to take a project from an idea to a fully developed research paper. Students learn how social scientists approach research, develop a research proposal, and do preliminary research in the first semester. Students conduct research and write up results as a research article in the second semester. Lectures address different empirical strategies, such as case studies and regression, as well as issues that arise in the course of research. In the second semester, half of the class sessions will be lectures on research design and strategies, and the other half will be hands-on writing and research workshops.

Introduction to Machine Learning for Social Scientists. Government Department Methods Workshop on April 19th, 2017. University of Texas at Austin. Slides (contact me for example code and data).

Machine learning is an increasingly common tool for data analysis. In this short course, we cover the basics of machine learning: what it is, why and how social scientists can use this family of methods, and what fits under the machine learning umbrella. We go through examples in R of decision trees and random forest classifiers. The course also covers useful techniques that can be integrated into any analysis, particularly parallelization and cross-validation. The course closes with a discussion of extensions to unsupervised learning, implementation in Python, and causal inference with machine learning, and suggests resources for students to continue learning on their own time.

Creating a Professional Website. Graduate Student Workshop on August 23rd, 2016. University of Texas at Austin. Slides.

Personal, professional websites describe your research interests, ongoing work, and accomplishments in a central location. Personal pages are most important for when prospective employers look you up online, but can also be useful for conferences, networking, and disseminating your research. This workshop compares different platforms and provides templates to get you started. We cover topics like how to SEO your page so it actually shows up when people Google you, why you should spend the $100 to host it in your name instead of getting a free site (and how to do that), and adding Google Analytics. 

Resources (these are the free online tools that I have used in my own work and recommend to others)

Job Market Guide (written by UT political science job candidates in 2017)

Making your own website:

Getting started with WordPress: Tutorial

Learn to code for free with Codecademy or Udacity.

Machine Learning for Political Scientists:

Computational Legal Studies (includes course slides and tutorials for starting from a social science background).

Intro to Machine Learning course from Udacity.

Muchlinski, D., Siroky, D., He, J., & Kocher, M. (2016). Comparing random forest with logistic regression for predicting class-imbalanced civil war onset data. Political Analysis24(1), 87-103. Link to article