- Multilevel Models, graduate level, Spring 2018, Spring 2021
- Quantitative Techniques in Political Science, graduate level, Fall 2017, Fall 2018, Fall 2019, Fall 2020
- Syllabus
- R Labs:

- Lab 1: Introduction to R & Reproducible Research
- Lab 2: Reading and Visualizing Data
- Lab 3: Vectors and Matrices
- Lab 4: Solving Linear Systems of Equations
- Lab 5: Functions, If Statements, and For Loops
- Lab 6: Representing Numbers in the Computer
- Lab 7: Multivariate Calculus & Optimization Problems
- Lab 8: Probability. Die and Decks of Cards. Card Games!
- Lab 9: Random Variables and Probability Distributions
- Lab 10: Descriptive Statistics & Visualization
- Lab 11: Hypothesis Testing
- Extra (in class): Integrals; Law of Large Numbers and Central Limit Theorem

- Quantitative Techniques in Political Science II, graduate level (Linear Regression), Spring 2019, Spring 2020, Spring 2021
- R Labs:

- Lab 1: Causality and Measurment
- Lab 2: The Basics of Linear Regression
- Lab 3: Diagnostics
- Lab 4: Visualization & Prediction
- Lab 5: Unusual Data
- Lab 6: Interactions
- Lab 7: Missing Data

- Generalized Linear Models, graduate level, Fall 2018,
- Syllabus
- R Labs:

- Lab 1: The Likelihood Model of Inference
- Lab 2: Binomial Models, Predicted Probabilites, and First Differences
- Lab 3: Calculation of Predicted Probabilities Using the Observed Value Approach
- Lab 4: Models for Count Outcomes: Poisson, Negative-Binomial, and Zero-inflated Models. Simulation of Predictions.
- Lab 5: Models for Unordered Categorical Dependent Variables. Simulation of Predictions.
- Lab 6: Models for Ordered Categorical Dependent Variables. Simulation of Predictions.
- Lab 7: Bootstrapping, Model Checking, Sensitivity Analysis, Cross-validation
- Lab 8: Missing Data

- Multilevel Models, graduate level, Spring 2017
- Bayesian and Frequentist Multilevel Models
- Syllabus

- Generalized Linear Models, graduate level, Fall 2016
- Mathematics for Political Science, graduate level, Fall 2016
- One credit course, mandatory for first year students
- Syllabus

- Multilevel Modeling for Quantitative Research, graduate level
- Professor: Jeff Gill
- Syllabus

- Measurement and Latent Trait Models, graduate level
- Professor: Jacob Montgomery

- Quantitative Political Methodology, undergraduate level
- Professor: Jacob Montgomery
- Syllabus

- An Introduction to R, University of Virginia, 2016
- Handling Non-English Text in Python, Methods Workshop, WUStL, 2014
- Web Mining with Python, WUStL, 2014
- An Introduction to Python, WUStL, 2012

- Politics of a Connected Public
- Professor: Betsy Sinclair
- Syllabus

- Latin American Politics Through Film
- Professor: Brian F. Crisp

- Presidents, Legislators, and Economic Policy in Latin America
- Professor: Brian F. Crisp