Teaching Experience

Recent Classes (2022-2023 Academic Year)

Politics and Technology (Undergraduate) - Spring 2023 | Syllabus

  • Summary: Through philosophy, social science, and fiction,  we will try to understand the role that technology played in shaping the state in democratic and authoritarian nations in the past and then turn our attention to the future, exploring technological innovations hatched during the digital revolution, such as artificial intelligence, which are transforming our society and culture at this very moment. 

  • Taught at: University of Georgia.

  • Overall Student Rating: 4.8/5.0

Big Data and Artificial Intelligence for Public Administration and Policy (Graduate) - Spring 2023 | Syllabus

  • Summary: The goal of this course is to provide an overview of some of the methods driving big data methodologies and to explore how these technologies are shaping and will shape the future of public policy and government with an eye towards the ethical dilemmas that these technologies raise. We begin the course with a discussion of some of the fundamental theories and applications of machine learning methods, which form the basis of big data and artificial intelligence technologies. We then move on to an in-depth discussion of the ethical and societal promises and perils that these technologies pose for decision making in government more broadly, focusing on the potential of these techniques to shape government and policy. 

  • Taught at: University of Georgia.

  • Overall Student Rating: 4.4/5.0

Advanced data science Courses

Machine Learning for Policy Analysis | Syllabus

  • Intro to Supervised Machine Learning; Intro to Unsupervised Machine Learning, Intro to Natural Langauge Processing, Intermediate Data Wrangling.

  • Taught at: Princeton University, University of Georgia.

Modern Text Analysis & Machine Learning for Policy Research | Syllabus

  • Natural Language Processing; Data Wrangling; Supervised Learning with Text Data; Unsupervised Learning with Text Data.

  • Taught at: University of Georgia

Applied Machine Learning | Syllabus

  • Intro to Supervised Machine Learning; Intro to Unsupervised Machine Learning; Intro to Natural Language Processing; Intermediate Data Wrangling.

  • Taught at: University of Calfornia, Berkeley.

Big Data and Artificial Intelligence in Public Policy | Syllabus

  • Intro to Supervised Machine Learning; Algorithmic Bias, Ethics and Governance.

  • Taught at: University of Georgia.

INTRODUCTORY DATA SCIENCE & STATISTICS COURSES

Introduction to Research Methods in Public Policy | Syllabus.

  • Introduction to research methods, experiments and causal inference.

  • Taught at: University of Georgia.

Data Applications for Public Policy | Syllabus.

  • Intro to Probability and Statistics; Linear and Logistic Regression; Intro to Data Acquisition and Data Wrangling.

  • Taught at: University of Georgia.

DATA SCIENCE BOOTCAMPS

Statistical Computing in Python | Syllabus

Python for Data Analysis | Syllabus

substantive courses