Teaching
This page combines current handbook-style course material with earlier university teaching in economics.
Handbook Short Courses
- Data Science Foundations for New Grads A self-paced handbook short course on the minimum practical knowledge needed to start working credibly in data science: probability, experiments, machine learning, SQL, coding, and product thinking.
- Applied Machine Learning for Tabular Data A self-paced handbook short course on problem framing, evaluation, feature engineering, trees, optimization, and model selection for tabular ML.
- Decision Trees and Ensemble Methods in Machine Learning A self-paced handbook short course on decision trees, random forests, feature importance, and boosting methods for structured data.
University Teaching Experience
Boston University, Department of Economics
Teaching Fellow, 2016-2020
- EC 202 Intermediate Macroeconomic Analysis (Undergraduate), Fall 2019, Spring 2020
- EC 102 Introductory Macroeconomic Analysis (Undergraduate), Spring 2019
- EC 502 Macroeconomics (Graduate), Fall 2016, Spring 2017, Fall 2017, Spring 2018
Universitat Pompeu Fabra, Department of Economics
Teaching Fellow, 2014-2015
- Microeconomics 2 (Undergraduate), Spring 2015
- Advanced Macroeconomics 1 (Undergraduate), Fall 2014, Spring 2015
Barcelona Graduate School of Economics
Teaching Fellow, 2014-2015
- Advanced Macroeconomics II (Graduate), Fall 2014
- Advanced Macroeconomics III (Graduate), Spring 2015
University of Melbourne, Department of Economics
Teaching Fellow, 2012
- Quantitative Methods 1 (Undergraduate), Semester 1 2012
Teaching Areas
- Macroeconomics
- Quantitative methods
- Applied machine learning for structured data
- Forecasting, experimentation, and decision-making
Course Materials
New handbook chapters, references, and teaching notes will continue to be published here.