We have all heard the phrase “correlation does not equal causation.” What, then, does equal causation? This course aims to answer that question and more!
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A Crash Course in Causality: Inferring Causal Effects from Observational Data
University of PennsylvaniaAbout this Course
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Try Coursera for BusinessSkills you will gain
- Instrumental Variable
- Propensity Score Matching
- Causal Inference
- Causality
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Syllabus - What you will learn from this course
Welcome and Introduction to Causal Effects
Confounding and Directed Acyclic Graphs (DAGs)
Matching and Propensity Scores
Inverse Probability of Treatment Weighting (IPTW)
Reviews
- 5 stars77.36%
- 4 stars18.72%
- 3 stars2.05%
- 2 stars0.82%
- 1 star1.02%
TOP REVIEWS FROM A CRASH COURSE IN CAUSALITY: INFERRING CAUSAL EFFECTS FROM OBSERVATIONAL DATA
It will be better to give reviews of related applications in specific AI areas (e.g, computer vision, NLP, etc.) at the end of each of the sections of the lesson.
The course is very simply explained, definitely a great introduction to the subject. There are some missing links, but minor compared to overall usefulness of the course.
Very easy to follow examples and great coverage for such an important topic! The delivery sometimes get repetitive and I wish we talked more about how the uncertainties are derived.
Great introduction to the field covering model synthesis of causality ideals. Glitches in assignments - make sure to check the discussion for workarounds.
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