Data 88E: Economic Models is a course offered at UC Berkeley as part of the Data Science Connector Course series. It’s designed to bridge the gap between data science and economics by using real-world datasets and Python programming to illustrate key economic concepts. The course is intended for students from both data science and economics backgrounds, giving them a chance to apply computational tools to economic models.
Students work with Python in Jupyter Notebooks to explore economic concepts such as supply and demand, market equilibrium, utility, game theory, and more. The course emphasizes how economic decisions are influenced by real-world data and policy interventions, making it a practical intersection of economics and data science.
As a connector course to the main Data 8 course, Data 88E labs mostly use a specific Python package developed at UC Berkeley for teaching. This package is known as datascience tables. Furthermore the notebooks also make extensive use of a Python package for automatic grading called otter-grader. Both packages are available from pypi using pip install XXX .
