Teaching
Instructor of Record
Introduction to Data Science for Business and Economics (Spring 2025)
Topics Covered:
| Part I :: Transformation to Analysis | Part II :: Explaining and Predicting |
|---|---|
| 1. Data fundamentals | 1. Regression fundamentals |
| 2. Beginning to learn | 2. Potential outcomes and causal inference |
| 3. Models for exploration | 3. Regression discontinuity |
| 4. Making inferences | 4. Difference-in-differences |
| 5. Measurement error, sample selection, and confounding | 5. Prediction with regression |
| 6. Bayesian approach to learning from data | 6. Introduction to machine learning |
Guest Lecturer
Introduction to Data Science for Business and Economics
- Bayesian Approach to Learning from Data (Fall 2024, Spring 2024, Fall 2023)
- Measurement Error and Sample Selection (Fall 2024)
Coordinating Graduate Assistant
Introduction to Data Science for Business and Economics (Fall 2024, Spring 2024, Fall 2023, Spring 2023, Fall 2022)
Teaching Assistant
Introduction to Data Science for Business and Economics (Fall 2025 and Spring 2022)
Intermediate Microeconomics (Spring 2022)
Principles of Microeconomics (Fall 2021)
Honors Principles of Microeconomics (Fall 2021)
Course Development
I have been part of the development team for the course “Introduction to Data Science for Business and Economics” since UGA started offering it in Spring 2022. This course is required for all Economics majors and for students completing the Area of Emphasis in Business Analytics, and it serves as a pathway to the Master’s of Business Analytics program.
As a team member, I have made several key contributions to course development. I developed, deployed, and maintain online R-based homework assignments and helped redesign our semester-long data science project to better align with course goals. I attended the 2023 Posit conference workshops on the team’s behalf to learn from a leading instructor on pedagogy and best practices for teaching data science. To enhance student understanding of computing environments and coding basics and prepare students for their final projects, I helped create two formative project assignments. I also built our exam grading system and edited the exam to accurately reflect course learning objectives.
I led our team’s efforts to incorporate AI-assisted grading tools like Gradescope as well as generative AI into the development of backend course administration and grading as well as in-class materials. These efforts enable the team to deliver comprehensive, efficient grading and feedback to 250 students each semester with minimal teaching assistant involvement, freeing up those resources for student-facing activities rather than administrative tasks.
Presentations
- Southern Economic Association Meetings (upcoming)
- University of Alabama at Birmingham AI Economics Summit (upcoming)
- Journal of Economics Teaching Symposium on Economics Teaching (2024)