AWS vs Google Cloud Certification for Machine Learning, Settled

Take the AWS Certified Machine Learning Engineer – Associate. AWS vs Google Cloud certification for ML: $150 against $200, a badge valid three years instead of two, and more learned on the way through. Google’s Professional Machine Learning Engineer wins in one situation: you work for, or want to work for, a Google Cloud partner, where the badge can be a hiring requirement rather than a nice-to-have. Both exams are mid-rewrite, so timing matters as much as the choice.

Before you spend $150 or $200 proving what you know, be sure you know it. Our free Machine Learning Fundamentals course covers what both exams assume you walked in with, and the Towards AI track picks up where it stops.

First, the exam most people are still searching for is gone

US search volume for “aws certified machine learning specialty” is still roughly 1,900 a month (Ubersuggest, pulled July 29, 2026). The exam behind it no longer exists. AWS retired MLS-C01 on March 31, 2026 and still says so at the top of its own page, checked August 5, 2026: existing holders keep an active certification for three years from the date they earned it, but nobody new can sit it.

AWS hasn’t finished tidying up after itself, either. The MLA-C01 page’s own FAQ still tells you that if you want to go deeper into machine learning, “we recommend AWS Certified Machine Learning – Specialty” — a recommendation to book an exam AWS cancelled four months ago. Read vendor certification pages the way you’d read a changelog.

The real 2026 matchup is one associate-level AWS exam against one professional-level Google exam: the AWS Certified Machine Learning Engineer – Associate (MLA-C01) against the Google Professional Machine Learning Engineer (PMLE), the only Google Cloud certification aimed squarely at ML engineers. Different weight classes on paper. In practice they compete for the same candidate, and the cheaper one usually wins. If you searched this as “GCP vs AWS certification,” it’s the same question. GCP is Google Cloud’s old name, and plenty of people never stopped using it.

AWS vs Google Cloud certification: the ML exams at a glance

Every figure in that table came off the vendors’ own pages, re-checked August 5, 2026: AWS MLA-C01 and Google PMLE. We did not sit either exam and won’t pretend otherwise. This is a document-verified comparison, scored against what people who did sit them reported publicly.

Price and renewal: AWS wins, and it isn’t close

$150 against $200 looks like a $50 argument. The renewal clock makes it a $300 one. (Both list prices verified on the vendors’ pages August 5, 2026; Google adds tax where applicable.)

AWS certifications run three years. Google’s professional certifications run two, and its renewal FAQ carries a detail that costs people money: the continuing-education renewal path in Google Skills covers exactly four certifications — Cloud Digital Leader, Associate Cloud Engineer, Professional Cloud Architect and Professional Data Engineer. The ML Engineer is not one of them. Google says it plans to extend the option to other certifications “at a later date” and gives no date. Until then you renew the PMLE by sitting the exam again, and only from 60 days before the badge goes inactive.

Over six years at August 2026 list prices, that’s $300 of AWS exams against $600 of Google exams. Both vendors soften it. AWS gives 50% off your next AWS certification once you hold one, per the FAQ on its own Specialty page; Google issues a 50% renewal code when you first certify, per the renewal FAQ. Neither closes the gap, because both discounts apply to the exam you were going to have to book anyway.

Difficulty: Google’s exam is easier than Google’s own page implies

Google recommends 3+ years of industry experience, including a year designing and managing Google Cloud solutions. Treat that as aspiration, not a gate.

On December 5, 2025 an r/googlecloud poster who had lost a dental-industry job two months earlier, and whose entire technical background was a computer-science minor of four introductory classes, described passing the PMLE after “studying intensely for about 2.5 weeks” on the Coursera course, practice quizzes and the official study guide. He supplied the caveat himself, which is why we trust the rest of it: “remember that I didn’t have a job and all the free time in the world.” Read that as full-time study. Hold down a job and the same material is more like six weeks of evenings, which is our arithmetic rather than his. He was equally clear-eyed about what the pass bought him: “a certification is a nice thing to have on a resume but is not enough to start a career in ML.”

A commenter on another thread put the exam’s character precisely. The questions are “less about machine learning math and more about choosing the right service given some constraints (hint: usually using the Google service is the right answer).” Worth knowing before you weigh that: the same commenter disclosed in the thread that he sells a PMLE practice-exam tool. We quote him because the observation matches the exam guide’s own emphasis on architecting and service selection, not because a vendor said it.

The AWS exam asks for more hours and gives back more. One candidate who posted his MLA-C01 pass report on May 26, 2026 logged “6 weeks to prepare, I think some 50 prep hours in total,” found roughly 30% overlap with the Solutions Architect Associate he’d sat two months earlier, and rated MLA-C01 easier than SAA-C03: “questions were shorter in length but also simpler.” In a June 16, 2026 thread, a holder of four AWS badges “scored in the 800s” and found the questions “concise and straightforward.” A third named the payoff: preparing for it “helped me learn Deep Learning, ML algorithms, and SageMaker in depth.”

Three of the four AWS passers we read volunteered the same side note, and it’s the most actionable line in either thread: the third-party question banks are harder than the exam. Tutorials Dojo, Frank Kane, Maarek, all rated tougher than the real thing. One of them put a number on it. Clear Tutorials Dojo at around 70% and you’re ready to book.

Notice what the two sets of reports are actually about. The Google passer talks about how fast he got through it. The AWS passers talk about what they came out knowing. Four threads is not a survey, but the split is clean enough to act on.

Winner on learning-per-dollar: AWS. Winner on fastest badge: Google, if speed is the thing you’re buying.

What each exam actually tests: AWS wins for engineers

Google’s page contradicts itself in the space of two paragraphs, and the contradiction is the most useful thing on it. First it describes the ML Engineer as a role with “strong programming skills.” Then it footnotes the exam: “The exam does not directly assess coding skill.” The six abilities it does assess are architect low-code AI solutions, collaborate across teams to manage data and models, scale prototypes into ML models, serve and scale models, automate and orchestrate ML pipelines, monitor AI solutions. “Low-code” is doing real work in that first line. Google is certifying that you can pick the right service, not that you can write the thing.

AWS aims lower and lands harder. MLA-C01 validates implementing ML workloads in production and operationalizing them, its stated candidate has “at least 1 year of experience using Amazon SageMaker and other ML engineering AWS services,” and it names those candidates as backend developers, DevOps engineers, data engineers, MLOps engineers and data scientists. Pass reports match: the questions were “mostly around SageMaker,” inside the tooling rather than above it.

So the credential you want depends on which half of the job you do. AWS is the closer match if you ship and babysit models. Google’s framing fits if your day is choosing managed services and defending the architecture in a review.

Career signal: AWS for the open market, Google for one specific employer

Here the cheaper exam doesn’t automatically win.

The most useful thing anyone has said about the PMLE came from a hiring manager on r/googlecloud on November 16, 2025. He opened by disclaiming the general case — “Can’t speak for industry as a whole” — and then said this: “But personally I’m hiring for my team right now and one requirement is that certification. For better or worse it can be a key for Google Cloud Partnership status, if you generally know your stuff and have a PMLE I can personally vouch that you’d be an instant top candidate.”

A second commenter in the thread described the mechanism from inside: “Usually, google forces their partners to get that certificate. So that they will give you more consulting customers.” A third, at an official Google partner, said the certs “add more weight to your resume.” Three people, one thread, all pointing at the same lane.

That’s rare, and it’s the whole Google case: a credential with a named buyer. At a Google Cloud partner the PMLE isn’t résumé decoration, it’s inventory the firm needs to hold a partnership tier.

Outside that circle the read is colder. A commenter who came back to the same thread in mid-2026 said that “in SOME cases” it helps you reach an interview, “IF you have a professional project in your resume. If no GCP project in your resume, it is unlikely to help.” Two conditionals in one sentence, both his. AWS runs the bigger cloud, so its badge lands in front of more employers by default, though that is an inference from market share and not a job-posting count we ran. If Microsoft’s stack is where your employers live, the AWS vs Azure comparison is the argument you need instead.

Winner: AWS for the general market, Google if a partner org is in your sights.

Timing: both exams are moving under your feet

Neither vendor wins here. This section will save you the most money.

AWS is mid-changeover. Registration for the updated MLA-C02 opens September 1, 2026, and the last day to sit MLA-C01 in English is September 28, 2026, both stated on AWS’s own exam page as of August 5, 2026. If you have already studied the current blueprint, book before the cutoff. If you’re starting from scratch, wait. Six weeks isn’t enough runway to learn a syllabus that’s about to be replaced. One detail that will catch people out: the Korean, Japanese and Simplified Chinese versions of MLA-C01 stay available past the English cutoff, until MLA-C02 reaches general availability.

Google’s exam has already changed. Its page states the exam was updated for the move from Vertex AI to the Gemini Enterprise Agent Platform, plus changes to the data and analytics stack, and that it “prioritizes Google Cloud native solutions.” Every practice bank written before that update is now partly wrong, and product renaming is what practice questions go stale on first. Note that the passer we quoted above sat the old version, in December 2025.

Here is the sharpest criticism of the AWS exam we could find, and it doesn’t survive contact with the thread it came from. In that June 16, 2026 discussion, a commenter relayed someone else’s claim that MLA-C01 is “intentionally misleading and difficult so takers have to retake it.” The poster went looking for the reasoning behind it and reported back: “there is no explanation. Even in chat he only mentioned that it’s difficult.” Meanwhile a passer in the same thread asked the obvious question — “If someone says it isn’t a good exam, I would question why.” Eleven comments is a thin sample either way, so treat this as a rumour we checked and could not stand up, not as an all-clear.

The real knock on the AWS exam is duller and better evidenced. It’s an Associate, and it reads like one: the May 2026 passer who holds both called it “easier than SAA-C03,” with shorter and simpler questions. You are buying a mid-tier badge on a blueprint with barely two months left in English. Google’s is a Professional-tier title that keeps its name. If what you need is the word on the certificate rather than the knowledge behind it, our recommendation flips, and we’d rather say so than pretend the price argument settles everything.

Choose the AWS ML Engineer Associate if…

• Your employer runs on AWS, or your target job descriptions name SageMaker.
• You want the credential to teach you something, not just certify you.
• You already hold SAA-C03 or plan to. One passer put the overlap at roughly 30%, and he sat both inside two months.
• You’d rather pay $150 every three years than $200 every two.
• You can either book before September 28, 2026 or wait for MLA-C02.

Choose the Google Professional ML Engineer if…

• You work at, or are applying to, a Google Cloud partner. That’s the whole case, and it’s a strong one.
• Your day job is architecture and service selection rather than pipeline code.
• Your stack is BigQuery and Vertex AI, now the Gemini Enterprise Agent Platform.
• You want a professional-tier title and accept the two-year clock.

We review both of these individually, at more length than a head-to-head allows: the Google Cloud ML Engineer certification scored on its own terms, and the cheaper AWS AI Practitioner if the associate exam is a step too far for now. The full AWS lineup and Google’s machine learning track map the paths around each. For the wider field ranked by cost and employer signal, start at our AI certifications hub. And what Reddit recommends for learning ML is worth ten minutes before you spend $200 on proving you already learned it.

Bottom line

AWS wins this on arithmetic: $50 cheaper today, a year longer on the badge, and it knocks 50% off whichever AWS exam you sit next. Google wins it on employment, in one lane, because Google Cloud partners hire against the PMLE when their partnership status leans on it. Pick the vendor your paycheck already runs on, then book around the version changes rather than through them. If neither answer feels obvious, that’s information rather than indecision: whether an AI certification is worth it at all is the prior question, and for most people it’s the cheaper one to answer first.

Neither exam makes you build anything. Our free Agentic AI course is project-first and ends in a Certificate of Completion, with no proctor session and no exam fee.

More head-to-heads in the course comparison index.

FAQ

Which is cheaper, the AWS or Google Cloud ML certification?

AWS. The Machine Learning Engineer – Associate exam is $150; Google’s Professional Machine Learning Engineer is $200 plus tax, both verified on the vendors’ pages August 5, 2026. The gap widens on renewal, because AWS badges last three years and Google’s professional badges last two. Six years at those prices: $300 on AWS, $600 on Google.

Is AWS machine learning certification worth it in 2026?

For engineers on AWS, yes. Two of the four passers we read credited the prep itself: Bedrock and SageMaker “at a deeper level,” and “Deep Learning, ML algorithms, and SageMaker in depth.” Not what people usually say about a vendor exam. Caveat: MLA-C02 registration opens September 1, 2026, and MLA-C01 leaves English on September 28, 2026.

What happened to the AWS Certified Machine Learning – Specialty?

AWS retired it on March 31, 2026. Existing holders keep an active certification for three years from the date they earned it, but the exam can no longer be booked. Its role passed to the Machine Learning Engineer – Associate. Guides still recommending MLS-C01 are out of date.

Does the Google Professional Machine Learning Engineer require coding?

Not directly. Google states the exam “does not directly assess coding skill,” though it assumes enough Python and SQL to read a code snippet in a question. It recommends three-plus years of industry experience, but that’s guidance, not a gate. Prerequisites are listed as none, and candidates with far less have passed.

Changelog

• 2026-08-05 — Second QA and humanization pass, run without trusting the first. All four vendor pages and all four Reddit threads re-fetched today; every figure and every quoted string re-matched at source, so verifiedAt and LastVerified move to 2026-08-05 and the date stamps in the body move with them. Corrections: the FAQ claim that “every pass report” credited the prep with real learning was false — two of four passers said it, and the page now quotes both of them instead; “about 30% of the material overlaps” was one candidate’s estimate stated as fact and is now attributed to him; “passed MLA-C01 on May 26, 2026” was the post date, not the pass date, and now says so; the claim that AWS’s installed base “gets its badge into more job descriptions” is now marked inline as an inference from market share rather than a count we ran; the career-signal comment’s month was derived from a relative Reddit stamp and is now given as mid-2026; and the Google passer’s job loss was two months before he posted, not “just”. Added, verified: three of the four AWS passers independently said the third-party question banks are harder than the exam, with the 70%-on-Tutorials-Dojo readiness marker — the single most actionable line in either thread, and it was sitting unused. The primary keyword now appears in the answer block, which is still 79 words.
• 2026-07-30 — QA and humanization pass. Every vendor figure re-fetched independently and confirmed: AWS MLA-C01 ($150 / 130 min / 65 questions / Associate / 3-year validity / candidate profile “at least 1 year of experience using Amazon SageMaker”), the MLA-C02 changeover dates, the MLS-C01 retirement notice, Google PMLE ($200 plus tax / two hours / 50–60 multiple choice and multiple select / prerequisites none / 3+ years recommended / English and Japanese), and Google’s renewal FAQ (professional exams valid two years; continuing-education renewal limited to CDL, ACE, PCA and PDE). All four Reddit threads re-fetched and every quote checked against its original thread, with absolute submission dates now in the body. Corrections made: the answer block’s claim about a “far deeper” prep ecosystem was unevidenced and was cut; “literal hiring requirement” was softened to what the one hiring manager actually said; the hiring manager’s own “can’t speak for industry as a whole” disclaimer was restored; the Google passer’s “I didn’t have a job and all the free time in the world” caveat was restored; a quoted commenter’s practice-exam business was disclosed; “two commenters confirmed the mechanism” was corrected to what each of the three commenters actually said; the table’s “coding tested? Yes” for AWS was an inference and now reports that AWS doesn’t address it; and prices are now date-stamped at each point of use. The MLA-C01 criticism was re-reported as a rumour that dissolved on inspection, with a separate, better-evidenced negative added in its place.
• 2026-07-29 — Page created. All specs verified live on the vendors’ own pages the same day: AWS MLA-C01 ($150 / 130 min / 65 questions / 3-year validity / MLA-C02 opening Sept 1, 2026 and MLA-C01 English delivery ending Sept 28, 2026), AWS MLS-C01 retirement (March 31, 2026), Google PMLE ($200 + tax / 2 hours / 50–60 questions / no prerequisites / Vertex AI → Gemini Enterprise Agent Platform rewrite), and Google’s renewal FAQ (professional certifications valid two years; ML Engineer excluded from the Google Skills continuing-education renewal path). Student sentiment mined from four old.reddit.com threads fetched this session; all eight sources are cited inline in the body as well as listed in sources. Keyword targets established from scratch — this page is not in PAGE_MANIFEST.md; probe table and BUILD verdict recorded in keywordValidation. No first-hand exam claim is made anywhere on the page.