860-0033-00L  Big Data for Public Policy

SemesterFrühjahrssemester 2021
DozierendeE. Ash, M. Guillot
Periodizitätjährlich wiederkehrende Veranstaltung
LehrspracheEnglisch
KommentarNur für Masterstudierende und Doktorierende.


KurzbeschreibungThis course provides an introduction to big data methods for public policy analysis. Students will put these techniques to work on a course project using real-world data, to be designed and implemented in consultation with the instructors.
LernzielMany policy problems involve prediction. For example, a budget office might want to predict the number of applications for benefits payments next month, based on labor market conditions this month. This course provides a hands-on introduction to the "big data" techniques for making such predictions.
InhaltMany policy problems involve prediction. For example, a budget office might want to predict the number of applications for benefits payments next month, based on labor market conditions this month. This course provides a hands-on introduction to the "big data" techniques for making such predictions. These techniques include:

-- procuring big datasets, especially through web scraping or API interfaces, including social media data;
-- pre-processing and dimension reduction of massive datasets for tractable computation;
-- machine learning for predicting outcomes, including how to select and tune the model, evaluate model performance using held-out test data, and report results;
-- interpreting machine learning model predictions to understand what is going on inside the black box;
-- data visualization including interactive web apps.

Students will put these techniques to work on a course project using real-world data, to be designed and implemented in consultation with the instructors.