Causal Inference for Data Science Certification

The Causal Inference for Data Science Certification is a free advanced-level, 25-minute skill test from Science of Apps. It tests causal inference for data science — potential outcomes and the fundamental problem of causal inference, average treatment effects, randomised experiments and A/B tests, confounding, selection and collider bias, directed acyclic graphs and the backdoor criterion, adjustment by regression, matching, propensity scores and inverse probability weighting, difference-in-differences and parallel trends, instrumental variables, regression discontinuity, synthetic control, heterogeneous effects and uplift modelling, sensitivity analysis, and tools such as DoWhy and EconML — written to Hernán and Robins' What If, Pearl's Primer and applied econometrics practice for 2026 and 2027. Score 70% or more on its 25 questions to earn a verifiable Causal Inference for Data Science certificate (SOA-CIDS). Every question is based on published standards and research — including Causal Inference: What If (Miguel Hernán and James Robins, Harvard), Causal Inference in Statistics: A Primer (Judea Pearl, Madelyn Glymour and Nicholas Jewell), statsmodels documentation (statsmodels) — and each answer is explained with its source.

Science of Apps offers a free Causal Inference for Data Science Certification, written for 2026 and 2027. It tests foundations, graphs and bias, adjustment methods, quasi-experimental designs and advanced topics and practice with 25 original scenario questions in all, each naming its published source; you get an instant score and a verifiable certificate with a credential ID you can add to LinkedIn.

Read the five skill areas on this page, then take the 25-minute test online — no fee, course or sign-up. You see every answer explained when you finish. Score 70% or more and you get a Causal Inference for Data Science certificate straight away, on screen, as a PDF and by email, with a credential ID anyone can verify.

Yes. The questions are original scenarios written by Science of Apps, and each one is based on a public source you can read: Causal Inference: What If (Miguel Hernán and James Robins, Harvard); Causal Inference in Statistics: A Primer (Judea Pearl, Madelyn Glymour and Nicholas Jewell); statsmodels documentation (statsmodels); Recommendations for the Conduct, Reporting, Editing and Publication of Scholarly Work (ICMJE). The source is shown under each question and linked in the answer review. Science of Apps doesn't copy questions from other tests.

Five skill areas with five questions each, drawn from a bank of 10 per area so a retake brings new questions: Foundations (Potential outcomes, Estimands and Randomised experiments); Graphs and Bias (DAGs, Confounding and Selection and colliders); Adjustment Methods (Regression and matching, Propensity scores and Weighting and doubly robust methods); Quasi-Experimental Designs (Difference-in-differences, Instrumental variables and Discontinuity and synthetic control); Advanced Topics and Practice (Heterogeneous effects, Sensitivity and robustness and Tools and communication). Every question is an original scenario written to the 2026–2027 standard, with the published source named under it.

Data scientist or analyst estimating impact, Experimentation or product analytics lead, Economist or policy evaluator, Health or epidemiology researcher and Machine learning engineer working on decisions. It suits students at leading universities, career switchers and experienced professionals who want quick, verifiable proof of Causal Inference for Data Science knowledge in 2026 and 2027.

CS and AI students at MIT, Stanford, CMU, Berkeley, IITs, Tsinghua and ETH are hired on depth beyond tool use: model internals, systems and hardware. Passing earns a founder-signed Science of Apps certificate with a credential ID and QR code that recruiters can verify.

Two variables can move together because of confounders that affect both, reverse causation or chance. Causal inference uses designs and assumptions — randomisation, DAGs, natural experiments — to isolate the effect of one variable on another.

A variable caused by two others. Conditioning on a collider (for example by filtering a dataset on it) can create a spurious association between its causes, so it should usually not be adjusted for.

Yes. The test is online, in English and free everywhere — people take it from India, the US, the UK, Europe, Africa, Latin America and Asia-Pacific. Your certificate is dated with your own local date and can be verified from anywhere at scienceofapps.com/certification/verify/.

25 questions — 5 from each of 5 skill areas — with a 25-minute limit. You need 70% (18 of 25) to pass and 90% for distinction.

We rate it Advanced: assumes years in the role or deep specialist knowledge. It has 25 scenario questions — 5 from each of 5 skill areas — and a 25-minute limit. You need 70% (18 of 25) to pass and 90% for distinction.

Nothing. There is no fee to take a test, to receive the certificate, to have it emailed or to verify it, and no sign-up.

On our server, not in your browser. The answers never reach the page until you submit, so a certificate can only be earned by passing. Each certificate gets a unique credential ID stored by Science of Apps.

You see your score for each area and every question with the correct answer and why, with the published source behind it. You can retake after 30 minutes, and the retake draws questions you haven't seen yet.

No. Every certificate is dated, so it always shows when you passed. Retake a test any time for a newer date or a higher score.

Yes. After you pass, Add to LinkedIn opens the Licenses & certifications form with the certificate name, Science of Apps as the issuer, the issue date, your credential ID and the verification link filled in. You can also download it as a PDF or PNG, and it's emailed to you as a PDF.

Every certificate has a credential ID and a QR code. Scanning it, or entering the ID at scienceofapps.com/certification/verify/, shows the holder's name, the certification, the score and the issue date from our records.

No. They are Science of Apps' own assessments of applied skill. They aren't issued by a university or standards body, and they work best alongside a portfolio that shows the skills in real work.