Applied Data Science: Decision-Making Beyond Prediction
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.
Topics
- Articulate common challenges in data science about and for people.
- Design, develop, and deploy data science models that effectively deal with such challenges.
Official roster learning outcomes
Prerequisites & course information
Recommended prerequisite: ENGRD 2700, CS 1380, or equivalent, and experience programming in Python. Recommended corequisite: INFO 5430 or CS 5785.
Sources
- Course catalogue ↗2026-2027