4 to 360 hours flexible workload
valid certificate in your country
What will I learn?
This Causal Inference Course provides practical tools to design and evaluate programmes with credible impact estimates. Learn DAGs, counterfactuals, matching, weighting, regression, and instrumental variables, plus data preparation, diagnostics, and robustness checks. Using R or Python, you will build reproducible workflows, communicate results clearly, and turn evidence into confident policy and investment decisions.
Elevify advantages
Develop skills
- Causal DAG design: build clean DAGs to expose bias and valid identification paths.
- Regression for impact: estimate robust treatment effects with clear economics focus.
- Matching and weighting: apply PS, IPW, and diagnostics for balanced comparisons.
- Instrumental variables: run 2SLS and defend LATE assumptions in policy settings.
- Reproducible causal workflows: code, document, and report transparent impact studies.
Suggested summary
Before starting, you can change the chapters and the workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.What our students say
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