Causal Inference
Using statistical and experimental methods to determine cause-and-effect relationships from observational and experimental data, beyond mere correlation.
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Why It Matters
AI excels at finding patterns and correlations, but determining what actually causes an outcome requires causal reasoning that most ML models fundamentally lack; this skill turns AI-generated correlations into actionable knowledge.
How to Get Started
Study "The Book of Why" by Judea Pearl, complete the Causal Inference specialization from Columbia or Duke on Coursera, and practice using Python's DoWhy or R's dagitty packages on real datasets.
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