Data Science Certification Test
Tests applied data science skill — statistics and experimental thinking, data wrangling in Python and SQL, machine learning modelling and evaluation, and communicating results — at the level employers expect from data scientists in 2026 and 2027. Pass to earn Data Science SOA-DATA.
- Intermediate difficulty.Assumes hands-on experience in the role.
- 20 scenario questions
- 20 minutes, timed
- 70% to pass · 90% for distinction
- Free no sign-up needed
- LinkedIn-ready · add it to your profile in one clickSee how ↓
What is the Data Science Certification Test?
2026–2027 skills: statistics, Python and SQL, feature engineering, and machine learning models.
The Data Science Certification Test is a free intermediate-level, 20-minute skill test from Science of Apps. It tests applied data science skill — statistics and experimental thinking, data wrangling in Python and SQL, machine learning modelling and evaluation, and communicating results — at the level employers expect from data scientists in 2026 and 2027. Score 70% or more on its 20 questions to earn a verifiable Data Science certificate (SOA-DATA). Every question is based on published standards and research — including Introductory Statistics 2e (OpenStax (Rice University)), Machine Learning Crash Course (Google for Developers), Machine Learning Crash Course: Precision and recall (Google for Developers) — and each answer is explained with its source.
Built for your job title
Data scientist, Junior data scientist, Data analyst moving into data science, Machine learning engineer and Analytics engineer — and anyone who wants quick, verifiable proof of Data Science knowledge for a CV or LinkedIn in 2026 and 2027.
- Data scientist
- Junior data scientist
- Data analyst moving into data science
- Machine learning engineer
- Analytics engineer
What the test covers
Four skill areas with 5 questions each, drawn from a bank of 10 per area, so a retake brings questions you haven't seen.
- 01
Statistics and Experimentation
25%- Distributions and inference
- Hypothesis testing
- A/B tests
- 02
Data Wrangling with Python and SQL
25%- pandas
- SQL joins and aggregation
- Data quality
- 03
Machine Learning Modelling
25%- Algorithms
- Feature engineering
- Validation
- 04
Evaluation and Communication
25%- Metrics
- Imbalanced data
- Storytelling and ethics
Based on published standards
The questions are original scenarios, and each one names the public standard, official guide or research it draws on — shown under the question while you answer, and linked in your review. These are the sources behind this test:
- Introductory Statistics 2eOpenStax (Rice University)8 questions
- Machine Learning Crash CourseGoogle for Developers3 questions
- Machine Learning Crash Course: Precision and recallGoogle for Developers3 questions
- Metrics and scoring: quantifying the quality of predictionsscikit-learn3 questions
- e-Handbook of Statistical MethodsNIST2 questions
- The SQL languagePostgreSQL2 questions
- Cross-validation: evaluating estimator performancescikit-learn2 questions
- Preprocessing datascikit-learn documentation2 questions
- Group by: split-apply-combinepandas documentation1 question
- Working with missing datapandas documentation1 question
- Merge, join, concatenate and comparepandas documentation1 question
- Common pitfalls and recommended practicesscikit-learn documentation1 question
- Time series / date functionalitypandas documentation1 question
- Window functions tutorialPostgreSQL1 question
- pandas user guidepandas1 question
- Scaling to large datasetspandas documentation1 question
- Clusteringscikit-learn documentation1 question
- Linear modelsscikit-learn documentation1 question
- Ensembles: gradient boosting, random forests and morescikit-learn1 question
- Decomposing signals in components (PCA and more)scikit-learn documentation1 question
- Tuning the hyper-parameters of an estimatorscikit-learn documentation1 question
- Permutation feature importancescikit-learn documentation1 question
- Hidden Technical Debt in Machine Learning SystemsSculley et al., NeurIPS (2015)1 question
Try a sample question
Splitting data into train and test sets before scaling prevents
- class imbalance
- multicollinearity
- data leakage
- overfitting to noise
Show the answer
C. data leakage — Fit preprocessing on training data only. The real test has 20 questions like this.
How the test works
20 minutes, 20 questions
One question per screen, with a progress bar and a countdown. Your progress is saved on this device if you need to pause.
Graded on our server
Answers reach the page only after you submit, so the certificate can only be earned by passing.
Every answer explained
Pass or not, you see every question with the right answer, why, and the source behind it. Pass mark 70%, distinction 90%.
Your certificate
Founder-signed, with a QR code and credential ID. Download PDF or PNG, add to LinkedIn, and it's emailed to you.
What you earn

Pass, then add it to LinkedIn in one click
No typing. The Add to LinkedIn button opens your profile’s Licenses & certifications form already filled in: the certificate name, Science of Apps as the issuer, the issue date, your credential ID and a link recruiters can use to verify it.
- 1Take the 20-minute test
- 2Score 70% or more
- 3Click Add to LinkedIn

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Frequently asked questions
What is the Data Science Certification Test?
The Data Science Certification Test is a free intermediate-level, 20-minute skill test from Science of Apps. It tests applied data science skill — statistics and experimental thinking, data wrangling in Python and SQL, machine learning modelling and evaluation, and communicating results — at the level employers expect from data scientists in 2026 and 2027. Score 70% or more on its 20 questions to earn a verifiable Data Science certificate (SOA-DATA). Every question is based on published standards and research — including Introductory Statistics 2e (OpenStax (Rice University)), Machine Learning Crash Course (Google for Developers), Machine Learning Crash Course: Precision and recall (Google for Developers) — and each answer is explained with its source.
How can I get a free Data Science certification in 2026?
Take the free Data Science Certification Test on Science of Apps. It tests statistics, Python and SQL, and feature engineering against a 2026–2027 syllabus, and passing earns a verifiable certificate you can add to LinkedIn.
How do I take the Data Science Certification Test for free?
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 certificate straight away, on screen, as a PDF and by email, with a credential ID anyone can verify.
Are the Data Science Certification Test questions based on real standards?
Yes. The questions are original scenarios written by Science of Apps, and each one is based on a public source you can read: Introductory Statistics 2e (OpenStax (Rice University)); Machine Learning Crash Course (Google for Developers); Machine Learning Crash Course: Precision and recall (Google for Developers); Metrics and scoring: quantifying the quality of predictions (scikit-learn); e-Handbook of Statistical Methods (NIST); The SQL language (PostgreSQL). The source is shown under each question and linked in the answer review. Science of Apps doesn't copy questions from other tests.
What does the Data Science Certification Test cover?
Four skill areas with five questions each, drawn from a bank of 10 per area so a retake brings new questions: Statistics and Experimentation (Distributions and inference, Hypothesis testing and A/B tests); Data Wrangling with Python and SQL (pandas, SQL joins and aggregation and Data quality); Machine Learning Modelling (Algorithms, Feature engineering and Validation); Evaluation and Communication (Metrics, Imbalanced data and Storytelling and ethics). Every question is an original scenario written to the 2026–2027 standard, with the published source named under it.
Who should take the Data Science Certification Test?
Data scientist, Junior data scientist, Data analyst moving into data science, Machine learning engineer and Analytics engineer. It suits anyone who wants a quick, verifiable way to show Data Science knowledge in 2026 and 2027, from students and career switchers to experienced professionals.
Is a data science certification worth it in 2026?
A certificate helps most when it proves applied skill — choosing the right statistical test, avoiding data leakage, picking the right metric. This test checks exactly those, so the credential reflects what hiring managers screen for.
Do I need to code to take this test?
No live coding, but the questions use Python (pandas, scikit-learn) and SQL snippets you should be able to read.
Can I take the Data Science Certification Test from any country?
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/.
How long is the Data Science Certification Test?
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.
How hard is the Data Science Certification Test?
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.
How much do Science of Apps certifications cost?
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.
How are the tests graded?
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.
What happens if I don't pass?
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.
Do the certificates expire?
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.
Can I add the certificate to LinkedIn?
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.
How can an employer verify my certificate?
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.
Are these accredited qualifications?
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.
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