860-0033-00L  Data Science for Public Policy: From Econometrics to AI

SemesterFrühjahrssemester 2024
DozierendeS. Galletta, E. Ash, C. Gössmann
Periodizitätjährlich wiederkehrende Veranstaltung
LehrspracheEnglisch
KommentarOnly for Master students and PhD students.



Lehrveranstaltungen

NummerTitelUmfangDozierende
860-0033-00 GData Science for Public Policy: From Econometrics to AI2 Std.
Do12:15-14:00LFW B 1 »
S. Galletta, E. Ash, C. Gössmann

Katalogdaten

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.
SkriptLink
KompetenzenKompetenzen
Fachspezifische KompetenzenVerfahren und Technologiengeprüft

Leistungskontrolle

Information zur Leistungskontrolle (gültig bis die Lerneinheit neu gelesen wird)
Leistungskontrolle als Semesterkurs
ECTS Kreditpunkte3 KP
PrüfendeE. Ash, S. Galletta, C. Gössmann
Formbenotete Semesterleistung
PrüfungsspracheEnglisch
RepetitionRepetition nur nach erneuter Belegung der Lerneinheit möglich.

Lernmaterialien

Keine öffentlichen Lernmaterialien verfügbar.
Es werden nur die öffentlichen Lernmaterialien aufgeführt.

Gruppen

Keine Informationen zu Gruppen vorhanden.

Einschränkungen

PlätzeMaximal 60
WartelisteBis 23.02.2024

Angeboten in

StudiengangBereichTyp
Comparative and International Studies MasterWahlfächerWInformation
Data Science MasterInterdisziplinäre WahlfächerWInformation
Doktorat Geistes-, Sozial- und StaatswissenschaftenVertiefung FachwissenW+Information
Science, Technology, and Policy MasterSozialwissenschaftliche FächerOInformation