Reasoning with Data trains students to turn messy real-world datasets and experiments into credible empirical claims, covering data wrangling and visualization, core inference and causal tools (potential outcomes, DAGs, experiments, regression), and modern frontiers (LLMs, causal ML, benchmarks, and quasi-experiments). The course puts special emphasis on developing the practical skills that students will need in data-facing roles.
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