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Learn the basic concepts of economics through Data Science applications and Python programming. This course covers applications in inequality and development, econometrics, game theory and oligopoly, environmental economics, and finance.
This third course in the Data Science and Economics series is based on a Connector Course taught at UC Berkeley as a Connector between the field of Economics and the popular Introduction to Data Science Course.
In this course we cover some advanced topics from upper division courses, but in an introductory way, with applied applications and datasets.
This course is of interest to the growing number of students interested in the overlap between Economics and Data Science. The course has some more advanced programming challenges, including the Lorenz Curve and Gini Coefficient, statsmodels package for econometrics, and using a finance API.
Each of the applications follows a unique applied dataset to illustrate the concepts that are learned in intermediate economics courses. Concepts of applied data analysis are illustrated in some advanced fields.
