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HomeCertificationsPMLEExam Domains

Google Cloud · Official Blueprint · Last reviewed May 2026

PMLE Exam Domains & Blueprint

The official Google Cloud PMLE exam covers 8 domains. The vendor does not publish percentage weights for these domains — treat each as an equal part of the exam blueprint.

Exam OverviewPractice TestStudy GuideSample QuestionsExam Domains

PMLE Domain Weight Summary

#DomainWeightQuestions
1Scaling prototypes into ML models
—
57 practice Q
2Automating and orchestrating ML pipelines
—
51 practice Q
3Collaborating within and across teams to manage data and models
—
45 practice Q
4Architecting low-code ML solutions
—
75 practice Q
5Collaborating to manage data and models
—
57 practice Q
6Serving and scaling models
—
95 practice Q
7Monitoring ML solutions
—
86 practice Q
8Solving business challenges with ML
—
40 practice Q

Detailed Domain Breakdown

Domain 1: Scaling prototypes into ML models

57 practice questions

Covers the topics, concepts, and applied skills examined under the Scaling prototypes into ML models domain. Study the official exam objectives and practise questions in this area to build confidence and accuracy before your exam.

Practice Scaling prototypes into ML models questions

Domain 2: Automating and orchestrating ML pipelines

51 practice questions

Covers the topics, concepts, and applied skills examined under the Automating and orchestrating ML pipelines domain. Study the official exam objectives and practise questions in this area to build confidence and accuracy before your exam.

Practice Automating and orchestrating ML pipelines questions

Domain 3: Collaborating within and across teams to manage data and models

45 practice questions

Covers the topics, concepts, and applied skills examined under the Collaborating within and across teams to manage data and models domain. Study the official exam objectives and practise questions in this area to build confidence and accuracy before your exam.

Practice Collaborating within and across teams to manage data and models questions

Domain 4: Architecting low-code ML solutions

75 practice questions

Covers the topics, concepts, and applied skills examined under the Architecting low-code ML solutions domain. Study the official exam objectives and practise questions in this area to build confidence and accuracy before your exam.

Practice Architecting low-code ML solutions questions

Domain 5: Collaborating to manage data and models

57 practice questions

Covers the topics, concepts, and applied skills examined under the Collaborating to manage data and models domain. Study the official exam objectives and practise questions in this area to build confidence and accuracy before your exam.

Practice Collaborating to manage data and models questions

Domain 6: Serving and scaling models

95 practice questions

Covers the topics, concepts, and applied skills examined under the Serving and scaling models domain. Study the official exam objectives and practise questions in this area to build confidence and accuracy before your exam.

Practice Serving and scaling models questions

Domain 7: Monitoring ML solutions

86 practice questions

Covers the topics, concepts, and applied skills examined under the Monitoring ML solutions domain. Study the official exam objectives and practise questions in this area to build confidence and accuracy before your exam.

Practice Monitoring ML solutions questions

Domain 8: Solving business challenges with ML

40 practice questions

Covers the topics, concepts, and applied skills examined under the Solving business challenges with ML domain. Study the official exam objectives and practise questions in this area to build confidence and accuracy before your exam.

Practice Solving business challenges with ML questions

How to Use Domain Weights in Your Study Plan

The vendor does not currently publish percentage weights for these domains, so Courseiva does not rank them by weight.

Work through each domain systematically — cover fundamentals first, then applied and scenario-based topics.

Never skip a domain regardless of perceived importance. Full coverage is required to pass.

Use Courseiva domain analytics to track your accuracy per domain and route extra questions to your weak areas.

Practice every PMLE domain

Courseiva tracks your accuracy per domain automatically and routes you toward your weakest areas — no manual configuration needed.

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PMLE Concept Guides

Google PMLE

The Google PMLE exam tests your ability to design and operate production machine learning systems — not just train models.