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Program comparison

Google Professional ML Engineer vs AWS MLA-C01: different clouds and experience levels

For a practitioner choosing a cloud ML engineering certification

These are not equivalent certification levels: Google recommends 3+ years of industry experience for its Professional exam, while AWS targets roughly one year for its Associate exam. Compare your platform and engineering responsibilities before the registration fee.

Facts side by side

Swipe or scroll the table to compare both programs.

Price and duration retain their stated scope.
FactProfessional Machine Learning EngineerAWS Certified Machine Learning Engineer - Associate
PriceUSD 200 (USD 200 for one certification exam registration/attempt, plus applicable tax. Optional preparation and repeat-attempt costs are separate. Currency is explicitly stated by the first-party Spanish localization.)Official source · checked USD 150 (USD 150 for one MLA-C01 attempt; English testing ends September 28, 2026. Japanese, Korean and Simplified Chinese continue until MLA-C02 general availability. Preparation is separate.)Official source · checked
Duration2 hours for the exam assessment; not preparation timeOfficial source · checked 130 minutes for the exam assessment; not preparation timeOfficial source · checked
LevelProfessionalOfficial source · checked AssociateOfficial source · checked
Credentialindustry certificationOfficial source · checked industry certificationOfficial source · checked
FormatProctored certification examOfficial source · checked Proctored certification examOfficial source · checked
PrerequisitesNone formally. Recommended: 3+ years of industry experience, including at least 1 year designing and managing solutions with Google Cloud.Official source · checked Provider describes an intended candidate with at least 1 year using Amazon SageMaker and other AWS ML-engineering services; the guide also recommends at least 1 year in a related role. No formal prerequisite is stated.Official source · checked

Provider-listed modules and exam domains

Professional Machine Learning Engineer

  • Architect low-code AI solutions — Exam domain / not a course module; no preparation duration stated. · Source
  • Collaborate within and across teams to manage data and models — Exam domain / not a course module; no preparation duration stated. · Source
  • Scale prototypes into ML models — Exam domain / not a course module; no preparation duration stated. · Source
  • Serve and scale models — Exam domain / not a course module; no preparation duration stated. · Source
  • Automate and orchestrate ML pipelines — Exam domain / not a course module; no preparation duration stated. · Source
  • Monitor AI solutions — Exam domain / not a course module; no preparation duration stated. · Source

AWS Certified Machine Learning Engineer - Associate

  • Data Preparation for Machine Learning — Exam domain / not a course module; 28% of the blueprint. · Source
  • ML Model Development — Exam domain / not a course module; 26% of the blueprint. · Source
  • Deployment and Orchestration of ML Workflows — Exam domain / not a course module; 22% of the blueprint. · Source
  • ML Solution Monitoring, Maintenance, and Security — Exam domain / not a course module; 24% of the blueprint. · Source

What the credentials are

Professional Machine Learning Engineer

Credential type
industry certification · Source
Credential
Professional Machine Learning Engineer · Source Source Source Source Source Source
Issuer
Google Cloud · Source Source Source Source Source Source
Sharing
Digital badge and certificate for social-media sharing; verified credentials can be managed and shared in the Google Cloud Credential Wallet. · Source
Expiry and renewal
2 years from certification. Renewal eligibility begins 60 days before expiration; renewal remains possible up to 30 days after the inactive date, not an extension of active status. Renewal by the applicable exam adds two years. · Source Source
Exam requirement
Pass the certification exam; the reviewed sources do not state the passing-score threshold. · Source Source Source Source Source Source

AWS Certified Machine Learning Engineer - Associate

Credential type
industry certification · Source
Credential
AWS Certified Machine Learning Engineer - Associate · Source Source Source
Issuer
Amazon Web Services · Source Source Source
Sharing
Credly digital badge; AWS says badges can be showcased on social media and email signatures. · Source
Expiry and renewal
3 years. Pass the latest version of the exam before expiry. · Source Source Source
Exam requirement
Pass the certification exam. · Source Source Source

Cost for the stated scope

Professional Machine Learning Engineer

Estimate for the stated payment scope: USD 200 × 1 = USD 200.

  • One certification exam attempt: USD 200 × 1 = USD 200. One exam registration/attempt, plus applicable tax; not complete preparation cost or a guarantee of passing. · Source

Scope: Optional preparation and repeat-attempt costs are separate. Total learning cost is unknown. · Source

Retakes: Repeat attempts are separate; no fixed retake fee is established in the reviewed sources. · Source

AWS Certified Machine Learning Engineer - Associate

Estimate for the stated payment scope: USD 150 × 1 = USD 150.

  • One MLA-C01 exam attempt: USD 150 × 1 = USD 150. One exam registration; not a guarantee of passing or complete preparation cost. · Source

Scope: Regular one-attempt fee only; optional preparation, taxes and retakes are not assumed. · Source

Who should skip these options

Professional Machine Learning Engineer

  • The exam does not directly assess coding skill; interpreting Python and SQL snippets is not a hands-on coding-performance test. · Source
  • This is the certification exam, not Google Skills path 17. Completing that preparation learning path is not the same as registering for, taking or passing the separate exam. · Source

AWS Certified Machine Learning Engineer - Associate

  • Choose training instead if you need a taught introduction: this offering is a certification assessment, not a course curriculum. · Source
  • Review the recommended practical background before booking; an exam registration does not provide the preparation needed for the listed implementation tasks. · Source

Match the cloud platform and the expected experience

Google Cloud's Professional Machine Learning Engineer and AWS Certified Machine Learning Engineer - Associate assess cloud-specific machine-learning work, but they are not interchangeable levels. Google recommends three or more years of industry experience, including at least one year designing and managing Google Cloud solutions. AWS describes an intended candidate with at least one year using SageMaker and related AWS services, and recommends a year in a related role. These are experience recommendations, not mandatory paid courses or formal enrollment prerequisites.

Google's assessed capabilities include low-code architecture, cross-team data and model management, scaling prototypes, model serving, pipeline orchestration and monitoring. AWS organizes its current MLA-C01 blueprint around data preparation, model development, deployment and orchestration, and monitoring, maintenance and security. Its guide excludes designing full end-to-end architecture and defining organization-wide ML strategy. Choose around responsibilities you already handle or need to validate; do not read the overlapping engineering vocabulary as proof that both exams test the same breadth.

Separate the assessment purchase from learning and practical evidence

Google's first-party Spanish exam page explicitly states USD 200 plus applicable tax for registration. AWS lists USD 150 for one current MLA-C01 attempt. Both figures concern one assessment attempt, with preparation, applicable taxes and repeat-attempt costs separate. Neither is a complete learning budget or a guarantee of earning the credential. The lower AWS registration fee does not establish better value for a Google Cloud role, and Google's Professional title does not by itself justify paying more for an AWS-focused role.

Google lists two hours and 50–60 multiple-choice or multiple-select questions; AWS lists 130 minutes and 65 questions. Those are assessment details, not preparation estimates. Google explicitly says its exam does not directly assess coding skill, although interpreting Python and SQL snippets requires proficiency. The separate Google Skills learning path provides preparation activities, not the certification exam itself. Use practical work or a portfolio separately if you need evidence of building and operating systems beyond an exam result.

Check maintenance and current exam versions without inventing succession

Google's Professional credential is valid for two years and supports digital badge, certificate and Credential Wallet sharing. AWS's Associate credential is valid for three years, has a Credly badge, and can be renewed by passing the latest exam version before expiry. Google's renewal eligibility begins 60 days before expiration; its limited renewal period after inactivity does not extend active credential status. Renewal discounts and eligibility conditions should not be treated as an unconditional fixed future price.

Keep the AWS comparison tied to current MLA-C01 rather than mixing its fee with a separate beta offer. English MLA-C01 testing ends September 28, 2026; the listed Asian-language versions continue until the updated exam reaches general availability. AWS's retired Machine Learning - Specialty is a different credential: the existence of this Associate option does not establish a direct successor, replacement or automatic conversion. Recheck availability before booking and choose the platform-specific assessment that matches your experience.

Which to choose if…

Professional Machine Learning Engineer

Choose Google Professional ML Engineer if you have the recommended professional experience and want assessment across Google Cloud ML architecture, cross-team work and production operations.

AWS Certified Machine Learning Engineer - Associate

Choose AWS MLA-C01 if your work centers on AWS ML engineering and the Associate blueprint matches your relevant experience and responsibilities.

Alternatives in the registry

Related by topic or level.

Official pages and editorial sources

Editorial checked . No commercial relationship is documented for this comparison.

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