AI and Machine Learning Model Evaluation Certification

The AI and Machine Learning Model Evaluation Certification is a free 20-minute skill test from Science of Apps. It tests how to evaluate ML models — precision, recall, F1, ROC-AUC, calibration, cross-validation, regression metrics, fairness slices and production monitoring. Score 70% or more on its 20 questions to earn a verifiable AI and Machine Learning Model Evaluation certificate (SOA-MLE). Every question is based on published standards and research — including Metrics and scoring: quantifying the quality of predictions (scikit-learn), 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.

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 AI and Machine Learning Model Evaluation 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: Metrics and scoring: quantifying the quality of predictions (scikit-learn); Machine Learning Crash Course (Google for Developers); Machine Learning Crash Course: Precision and recall (Google for Developers); e-Handbook of Statistical Methods (NIST); AI Risk Management Framework (NIST); People + AI Guidebook (Google PAIR). 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: Classification and regression metrics (Precision, recall and F1, ROC-AUC and thresholds and Regression errors); Robust evaluation (Cross-validation, Calibration and slices and Monitoring in production); Fairness, explainability and robustness (Fairness metrics, Feature attribution and Adversarial robustness); Ranking, forecasting and business metrics (Ranking metrics, Forecast accuracy and Cost-sensitive evaluation). Every question is an original scenario based on a published standard, official documentation or research, named under the question.

Data scientist, ML engineer, AI researcher, Analytics lead and Model risk analyst. It suits anyone who wants a quick, verifiable way to show AI and Machine Learning Model Evaluation skills, from students and career switchers to experienced professionals.

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 Advanced: assumes years in the role or deep specialist knowledge. 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.

Senior data science and ML interviews in 2027 test model evaluation as judgement: choosing metrics that match the cost of errors (precision, recall, F1, PR-AUC, ROC-AUC, MAE or MAPE), validating without leakage, checking calibration and performance by slice, measuring fairness, and monitoring after launch. Practise explaining trade-offs with real numbers, learn the traps of accuracy and imbalanced data, and prove it with a verified test and an honest evaluation write-up. Our full career guide covers the hiring process, interview loop, pay and a prep plan: scienceofapps.com/blog/ml-model-evaluation-career-guide/

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.