AWS Machine Learning Certification Test
Tests applied machine learning skills on AWS — data engineering with S3, Glue, Kinesis and Athena, exploratory analysis and feature engineering, choosing and tuning models in SageMaker AI, ML implementation and operations under the Well-Architected ML Lens, and AWS AI services such as Rekognition, Comprehend and Textract. Pass to earn Machine Learning on AWS SOA-AWML.
- 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 AWS Machine Learning Certification Test?
The AWS Machine Learning Certification Test is a free advanced-level, 25-minute skill test from Science of Apps. It tests applied machine learning skills on AWS — data engineering with S3, Glue, Kinesis and Athena, exploratory analysis and feature engineering, choosing and tuning models in SageMaker AI, ML implementation and operations under the Well-Architected ML Lens, and AWS AI services such as Rekognition, Comprehend and Textract. Score 70% or more on its 25 questions to earn a verifiable Machine Learning on AWS certificate (SOA-AWML). Every question is based on published standards and research — including Machine Learning Crash Course (Google for Developers), Machine Learning Lens – AWS Well-Architected (Amazon Web Services), Amazon SageMaker AI (Amazon Web Services) — and each answer is explained with its source.
Built for your job title
Machine learning engineer, Data scientist, ML specialist, Cloud AI engineer and MLOps engineer — and anyone who wants quick, verifiable proof of AWS Machine Learning skills for a CV or LinkedIn.
- Machine learning engineer
- Data scientist
- ML specialist
- Cloud AI engineer
- MLOps engineer
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
Data Engineering on AWS
20%- Storage and ingestion
- Transformation
- Querying
- 02
Exploratory Data Analysis and Features
20%- Analysis
- Feature engineering
- Labelling
- 03
Modelling
20%- Algorithm choice
- Training
- Tuning
- 04
ML Implementation and Operations
20%- Deployment
- Security
- Cost and reliability
- 05
AWS AI Services
20%- Vision
- Language
- Specialised services
Independent skills test. Science of Apps is not affiliated with, endorsed by or sponsored by Amazon Web Services, Inc. Product and exam names are trademarks of their owners. Passing earns a Science of Apps certificate, not a certification issued by Amazon Web Services, Inc.
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:
- Machine Learning Crash CourseGoogle for Developers7 questions
- Machine Learning Lens – AWS Well-ArchitectedAmazon Web Services5 questions
- Amazon SageMaker AIAmazon Web Services4 questions
- Built-in algorithms and pretrained models in Amazon SageMakerAmazon Web Services4 questions
- AWS AI servicesAmazon Web Services4 questions
- Amazon Athena user guideAmazon Web Services2 questions
- AWS Glue developer guideAmazon Web Services2 questions
- Introductory Statistics 2eOpenStax (Rice University)2 questions
- Ensembles: gradient boosting, random forests and morescikit-learn2 questions
- Amazon Data Firehose developer guideAmazon Web Services1 question
- Amazon EMR management guideAmazon Web Services1 question
- AWS Step Functions developer guideAmazon Web Services1 question
- Amazon Kinesis Data Streams developer guideAmazon Web Services1 question
- Text feature extractionscikit-learn documentation1 question
- Decomposing signals in components (PCA and more)scikit-learn documentation1 question
- Amazon SageMaker Ground TruthAmazon Web Services1 question
- Prepare data with Data WranglerAmazon Web Services1 question
- Automatic model tuning with SageMaker AIAmazon Web Services1 question
- Amazon SageMaker Model MonitorAmazon Web Services1 question
- Inference options in Amazon SageMaker AIAmazon Web Services1 question
- Model RegistryAmazon Web Services1 question
- Amazon Rekognition developer guideAmazon Web Services1 question
- Amazon Comprehend developer guideAmazon Web Services1 question
- Amazon Textract developer guideAmazon Web Services1 question
- Amazon Personalize developer guideAmazon Web Services1 question
- Amazon Augmented AI (A2I)Amazon Web Services1 question
- Amazon BedrockAmazon Web Services1 question
Try a sample question
A team needs to label 50,000 images with a mix of human workers and automated labelling. The AWS service built for this is
- Amazon Comprehend
- SageMaker Ground Truth
- Amazon Rekognition Video
- AWS Glue DataBrew
Show the answer
B. SageMaker Ground Truth — Active learning plus human labellers. 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

Machine Learning on AWS
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Frequently asked questions
What is the AWS Machine Learning Certification Test?
The AWS Machine Learning Certification Test is a free advanced-level, 25-minute skill test from Science of Apps. It tests applied machine learning skills on AWS — data engineering with S3, Glue, Kinesis and Athena, exploratory analysis and feature engineering, choosing and tuning models in SageMaker AI, ML implementation and operations under the Well-Architected ML Lens, and AWS AI services such as Rekognition, Comprehend and Textract. Score 70% or more on its 25 questions to earn a verifiable Machine Learning on AWS certificate (SOA-AWML). Every question is based on published standards and research — including Machine Learning Crash Course (Google for Developers), Machine Learning Lens – AWS Well-Architected (Amazon Web Services), Amazon SageMaker AI (Amazon Web Services) — and each answer is explained with its source.
How do I take the AWS Machine Learning Certification Test 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 Machine Learning on AWS certificate straight away, on screen, as a PDF and by email, with a credential ID anyone can verify.
Are the AWS Machine Learning 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: Machine Learning Crash Course (Google for Developers); Machine Learning Lens – AWS Well-Architected (Amazon Web Services); Amazon SageMaker AI (Amazon Web Services); Built-in algorithms and pretrained models in Amazon SageMaker (Amazon Web Services); AWS AI services (Amazon Web Services); Amazon Athena user guide (Amazon Web Services). 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 AWS Machine Learning Certification Test cover?
Five skill areas with five questions each, drawn from a bank of 10 per area so a retake brings new questions: Data Engineering on AWS (Storage and ingestion, Transformation and Querying); Exploratory Data Analysis and Features (Analysis, Feature engineering and Labelling); Modelling (Algorithm choice, Training and Tuning); ML Implementation and Operations (Deployment, Security and Cost and reliability); AWS AI Services (Vision, Language and Specialised services). Every question is an original scenario based on a published standard, official documentation or research, named under the question.
Who should take the AWS Machine Learning Certification Test?
Machine learning engineer, Data scientist, ML specialist, Cloud AI engineer and MLOps engineer. It suits anyone who wants a quick, verifiable way to show AWS Machine Learning skills, from students and career switchers to experienced professionals.
Can I use this for machine learning on AWS exam, AWS ml certification practice test or sagemaker certification test?
Yes. The AWS Machine Learning Certification Test 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 AWS Machine Learning 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 AWS Machine Learning Certification Test?
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 AWS Machine Learning Certification Test?
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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