from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
This Causal Inference Course equips you with practical tools to design and assess programmes with reliable impact estimates. You will learn about DAGs, counterfactuals, matching, weighting, regression, and instrumental variables, along with preparing data, running diagnostics, and performing robustness checks. Using R or Python, you will create reproducible workflows, communicate findings clearly, and use evidence to make sound policy and investment decisions.
Elevify advantages
Develop skills
- Causal DAG design: construct clear DAGs to reveal bias and valid identification paths.
- Regression for impact: estimate strong treatment effects with a sharp economics focus.
- Matching and weighting: use PS, IPW, and diagnostics for balanced comparisons.
- Instrumental variables: implement 2SLS and justify LATE assumptions in policy contexts.
- Reproducible causal workflows: code, document, and report transparent impact studies.
Suggested summary
Before starting, you can change the chapters and 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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