Establishing causal claims and evaluating systems and models are at the core of modern Computer Science research. This course provides a rigorous introduction to empirical methods, combining foundational theory on causal inference with practical applications. Topics include causal diagrams, experimental and quasi-experimental designs, regression analysis, and benchmarks. Evaluation is based on weekly programming assignments, active class participation, and a final paper in which students develop and motivate a research project proposal.
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