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PMLEProfessional Machine Learning Engineer
Google Cloud Certified - Professional Machine Learning Engineer
ProfessionalAvailableAdvanced (designing and operating ML models, pipelines, MLOps and generative AI; coding isn't tested directly)60–100 hours (rough estimate by this site)
Data scientists, ML engineers, and MLOps and data platform engineers.
The exam has been updated to reflect the move from Vertex AI to Gemini Enterprise Agent Platform and changes to data and analytics services. This course follows the new exam guide (dated June 1, 2026).
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Progress by domain
Domain weights are from the exam guide. Progress is your practice record in this browser.
| Domain (weight) | Questions | Practice progress | Action |
|---|---|---|---|
| Section 1: Architecting low-code AI solutions約13% | 36 | Not answered | Practice |
| Section 2: Collaborating within and across teams to manage data and models約16% | 47 | Not answered | Practice |
| Section 3: Scaling prototypes into ML models約21% | 65 | Not answered | Practice |
| Section 4: Serving and scaling models約20% | 58 | Not answered | Practice |
| Section 5: Automating and orchestrating ML pipelines約18% | 54 | Not answered | Practice |
| Section 6: Monitoring AI solutions約13% | 39 | Not answered | Practice |
Original question bank: 299 questions (multiple choice 15, ordering 0, minimal pairs 104, case studies 3 with 9 questions). Mock exam: 60 questions · 120 min. Uses the upper limit stated on the exam page: 60 questions, 2 hours (the real exam has 50–60 questions).
Exam basics (checked 2026-10-10)
- Certification
- Google Cloud Certified - Professional Machine Learning Engineer
- Exam
- Professional Machine Learning Engineer（Google Cloud 認定資格）
- Level
- Professional
- Role
- ML engineers who build, productionize and operate ML and generative AI solutions on Google Cloud
- Duration
- 2 hours (per exam page)
- Format
- 50–60 multiple-choice and multiple-select questions. Online proctored or at a test center (per exam page)
- Passing
- Not stated on the exam page
- Cost
- USD 200 (plus tax) (per exam page)
- Languages
- English, Japanese
- Prerequisites
- No prerequisites. Recommended: 3+ years of industry experience, including 1+ year on Google Cloud (per exam page).
Reference links (checked 2026-10-10)
- Professional ML Engineer exam page: https://cloud.google.com/learn/certification/machine-learning-engineer
- Exam guide (English, PDF, dated June 1, 2026): https://services.google.com/fh/files/misc/professional_machine_learning_engineer_exam_guide_english_new.pdf
Facts on this page (names, exam codes, domains, weights, duration, passing score) are based on the public pages above and may change.
Notes (unofficial, original questions, no pass guarantee)
- The questions on this site are original practice questions written by this site based on publicly available skills outlines and exam guides. They are not actual exam questions.
- Google Cloud, Gemini, Vertex AI and Google Workspace are trademarks of Google LLC. This site is not affiliated with or endorsed by Google.
- This content is a study aid and does not guarantee a pass. Exam content, format and prerequisites may change without notice; always check the latest information on the official page before taking the exam.
- Your accuracy on the mock exam cannot be converted to the official (scaled) score and does not predict a pass or fail.
- Progress is saved only in this browser (localStorage) unless you sign in with Google to sync it. You can delete it from the Cookie & storage settings page (Japanese).