Data Science for Social Good Certification

The Data Science for Social Good Certification is a free intermediate-level, 20-minute skill test from Science of Apps. It tests data science for social good — scoping problems with NGOs and public agencies, theory of change and impact measurement, working with administrative and survey data, data quality and missingness, fairness and bias in predictive models, equity-aware evaluation, privacy, consent and data protection for vulnerable groups, open data and data-sharing agreements, causal evaluation of programmes, communicating with non-technical stakeholders, deployment and sustainability in low-resource settings, and responsible use of AI for public benefit — written to CMU DSSG, UN SDG, NIST and OECD guidance for 2026 and 2027. Score 70% or more on its 20 questions to earn a verifiable Data Science for Social Good certificate (SOA-DSSG). Every question is based on published standards and research — including Data Science for Social Good resources (Carnegie Mellon University DSSG), Towards a Standard for Identifying and Managing Bias in AI (SP 1270) (NIST), AI Risk Management Framework (NIST) — and each answer is explained with its source.

Science of Apps offers a free Data Science for Social Good Certification, written for 2026 and 2027. It tests scoping and impact, data and fairness, ethics, privacy and sharing and evaluation, communication and sustainability with 20 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 four skill areas on this page, then take the 20-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 Data Science for Social Good 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: Data Science for Social Good resources (Carnegie Mellon University DSSG); Towards a Standard for Identifying and Managing Bias in AI (SP 1270) (NIST); AI Risk Management Framework (NIST); General Data Protection Regulation (full text) (gdpr-info.eu); OECD AI Principles (OECD); The 17 Sustainable Development Goals (United Nations). The source is shown under each question and linked in the answer review. Science of Apps doesn't copy questions from other tests.

Four skill areas with five questions each, drawn from a bank of 10 per area so a retake brings new questions: Scoping and Impact (Problem scoping, Theory of change and Measuring impact); Data and Fairness (Administrative and survey data, Data quality and Fairness and bias); Ethics, Privacy and Sharing (Privacy and consent, Data sharing and Responsible AI); Evaluation, Communication and Sustainability (Programme evaluation, Communication and Deployment and sustainability). Every question is an original scenario written to the 2026–2027 standard, with the published source named under it.

Data scientist working with NGOs or government, Public sector or civic tech analyst, Researcher in development or public policy, Nonprofit monitoring and evaluation professional and Student interested in social impact. It suits students at leading universities, career switchers and experienced professionals who want quick, verifiable proof of Data Science for Social Good knowledge in 2026 and 2027.

Math, stats and economics majors are drawn to sports analytics, social-good data work and geospatial science. Passing earns a founder-signed Science of Apps certificate with a credential ID and QR code that recruiters can verify.

Projects serve public or nonprofit goals, often with vulnerable populations, limited resources and high stakes, so scoping, fairness, privacy, partner capacity and long-term sustainability matter as much as model accuracy.

Models used for decisions such as inspections, benefits or child welfare can reinforce historical bias, so teams must measure performance across groups and design interventions that do not harm already disadvantaged people.

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/.

20 questions — 5 from each of 4 skill areas — with a 20-minute limit. You need 70% (14 of 20) to pass and 90% for distinction.

We rate it Intermediate: assumes hands-on experience in the role. It has 20 scenario questions — 5 from each of 4 skill areas — and a 20-minute limit. You need 70% (14 of 20) 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.