Applied Data Science: Decision-Making Beyond Prediction

Catalog description

This course considers the data science challenges beyond training an accurate predictive model, especially for systems about people (data of behavior), and for people (deployed models to influence behavior). Whether for online marketplaces, transportation, governmental, or urban systems, effective data science in such settings requires dealing with user incentives and strategic behavior, networked and decentralized decision-making, and privacy and ethics concerns. Primary evaluation will be through programming based assignments (in Python) and conceptual questions.