Education

CADI Lab is committed to training the next generation of researchers and practitioners in causal inference, data science, and digital platform research. Our educational initiatives span graduate-level courses, hands-on research training, and more.

Courses

ISS5096 Methods

Experiments and Causal Inference

Spring Thursday, 14:20–17:20 TSMC Building, Room R406 Graduate

A graduate seminar on experimental and quasi-experimental designs for causal inference. This course introduces methods widely used in domains such as marketing, information systems, and the social sciences for establishing cause-and-effect relationships from data.

Key Topics

Randomized Controlled Trials (RCT) Difference-in-Differences (DiD) Matching Methods (PSM, CEM) Regression Discontinuity Design (RDD) Instrumental Variables (IV) Causal Machine Learning DAGs & Causal Mechanisms Panel Data & Fixed Effects
Syllabus Course Homepage
ISS4066 / ISS5066 Skills

Programming for Business Analytics

Fall Monday, 14:20–17:20 TSMC Building, Room R421 Undergraduate / Graduate

This course introduces the basics of programming using R for business applications. It equips students with fundamental skills for robust business data analysis, addressing both practical programming skills and conceptual understanding necessary to apply data science effectively in business contexts.

Key Topics

R Programming Fundamentals Data Wrangling & Visualization Causality & Regression Statistical Uncertainty Bootstrapping vs. CLT Professional Workflow (R, RStudio, Git, GitHub)
Syllabus