1 credit
Spring 2026 Distance Learning Upper Division
The main goal of this course is to extend the computational and programming toolkit developed in Quantitative Economics with Python. In particular, we will cover advanced methods for working with, visualizing and analyzing data in Python. In addition, we will consider more advanced programming techniques including stochastic optimization and infinite-horizon dynamic programming. Throughout the course we will consider a number of applications related to microeconomics, macroeconomics, and econometrics covered in the MS Econ program curriculum.
Learning Outcomes1Have working knowledge of programming techniques in Python.
2Have the ability to use scientific computing packages to analyze economic data.
3Have an understanding of numerical methods used to solve economic models.
4Use visualization tools to communicate computational results.
Restrictions
made by Purdue students.