MLOps Certification
Tests MLOps — ML pipelines and automation maturity, data and feature management, experiment tracking, reproducibility and model registries, CI/CD and deployment patterns for models, and production monitoring for drift and model performance. Pass to earn MLOps SOA-MLOP.
- Advanced difficulty.Assumes years in the role or deep specialist knowledge.
- 25 scenario questions
- 25 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 MLOps Certification?
The MLOps Certification is a free advanced-level, 25-minute skill test from Science of Apps. It tests MLOps — ML pipelines and automation maturity, data and feature management, experiment tracking, reproducibility and model registries, CI/CD and deployment patterns for models, and production monitoring for drift and model performance. Score 70% or more on its 25 questions to earn a verifiable MLOps certificate (SOA-MLOP). Every question is based on published standards and research — including MLOps: continuous delivery and automation pipelines in machine learning (Google Cloud), Site Reliability Engineering (Google), Databricks documentation (Databricks) — and each answer is explained with its source.
Built for your job title
MLOps engineer, Machine learning engineer, Data engineer, Platform engineer and ML team lead — and anyone who wants quick, verifiable proof of MLOps skills for a CV or LinkedIn.
- MLOps engineer
- Machine learning engineer
- Data engineer
- Platform engineer
- ML team lead
What the test covers
Five skill areas with 5 questions each, drawn from a bank of 10 per area, so a retake brings questions you haven't seen.
- 01
ML Pipelines and Automation
20%- MLOps maturity
- Pipeline orchestration
- Continuous training
- 02
Data, Features and Experiments
20%- Feature stores
- Experiment tracking
- Data and model versioning
- 03
Deployment Patterns
20%- Batch and online serving
- Release strategies
- Scaling and performance
- 04
CI/CD for Machine Learning
20%- Testing ML code and data
- CI/CD pipelines
- Governance and approvals
- 05
Monitoring and Model Performance
20%- Data and concept drift
- Performance monitoring
- Retraining and incident response
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:
- MLOps: continuous delivery and automation pipelines in machine learningGoogle Cloud19 questions
- Site Reliability EngineeringGoogle8 questions
- Databricks documentationDatabricks5 questions
- AI Risk Management FrameworkNIST5 questions
- The Practical Test PyramidMartin Fowler2 questions
- Docker: Get startedDocker Docs1 question
- What is Terraform?HashiCorp1 question
- Medallion architectureDatabricks1 question
- Machine Learning Crash CourseGoogle for Developers1 question
- Trustworthy Online Controlled ExperimentsKohavi, Tang & Xu1 question
- Kubernetes conceptskubernetes.io (CNCF)1 question
- OpenAPI SpecificationOpenAPI Initiative1 question
- Quantization overviewHugging Face1 question
- OWASP Cheat Sheet SeriesOWASP1 question
- e-Handbook of Statistical MethodsNIST1 question
- People + AI GuidebookGoogle PAIR1 question
Try a sample question
In Google's MLOps maturity model, level 1 adds
- full CI/CD for pipeline code plus automated retraining
- automated pipelines that retrain models on new data (continuous training)
- a manual notebook-based process with hand-off to engineers
- a single model trained once and never updated
Show the answer
B. automated pipelines that retrain models on new data (continuous training) — Level 0 is manual; level 2 adds CI/CD of the pipeline itself. The real test has 25 questions like this.
How the test works
25 minutes, 25 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 25-minute test
- 2Score 70% or more
- 3Click Add to LinkedIn

MLOps
Science of Apps
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Frequently asked questions
What is the MLOps Certification?
The MLOps Certification is a free advanced-level, 25-minute skill test from Science of Apps. It tests MLOps — ML pipelines and automation maturity, data and feature management, experiment tracking, reproducibility and model registries, CI/CD and deployment patterns for models, and production monitoring for drift and model performance. Score 70% or more on its 25 questions to earn a verifiable MLOps certificate (SOA-MLOP). Every question is based on published standards and research — including MLOps: continuous delivery and automation pipelines in machine learning (Google Cloud), Site Reliability Engineering (Google), Databricks documentation (Databricks) — and each answer is explained with its source.
How do I take the MLOps Certification for free?
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 MLOps certificate straight away, on screen, as a PDF and by email, with a credential ID anyone can verify.
Are the MLOps Certification 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: MLOps: continuous delivery and automation pipelines in machine learning (Google Cloud); Site Reliability Engineering (Google); Databricks documentation (Databricks); AI Risk Management Framework (NIST); The Practical Test Pyramid (Martin Fowler); Docker: Get started (Docker Docs). 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 MLOps Certification cover?
Five skill areas with five questions each, drawn from a bank of 10 per area so a retake brings new questions: ML Pipelines and Automation (MLOps maturity, Pipeline orchestration and Continuous training); Data, Features and Experiments (Feature stores, Experiment tracking and Data and model versioning); Deployment Patterns (Batch and online serving, Release strategies and Scaling and performance); CI/CD for Machine Learning (Testing ML code and data, CI/CD pipelines and Governance and approvals); Monitoring and Model Performance (Data and concept drift, Performance monitoring and Retraining and incident response). Every question is an original scenario based on a published standard, official documentation or research, named under the question.
Who should take the MLOps Certification?
MLOps engineer, Machine learning engineer, Data engineer, Platform engineer and ML team lead. It suits anyone who wants a quick, verifiable way to show MLOps skills, from students and career switchers to experienced professionals.
Can I use this for MLOps course, MLOps interview questions or MLOps quiz?
Yes. The MLOps Certification is free and covers all of these: 25 scenario questions in 25 minutes, each answer explained with the source it comes from, so it works as interview and exam practice. It isn't a full course, so use the areas you miss as your study list. Scoring 70% or more earns a verifiable certificate.
Can I take the MLOps Certification 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 MLOps Certification?
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.
How hard is the MLOps Certification?
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.
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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