Learn with Google : Professional-Machine-Learning-Engineer training material for 100% pass

Updated: Aug 20, 2026

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Google Professional-Machine-Learning-Engineer Exam Syllabus Topics:

TopicDetails
Topic 1
  • Monitoring ML solutions: It identifies risks to ML solutions. Moreover, the topic discusses monitoring, testing, and troubleshooting ML solutions.
Topic 2
  • Scaling prototypes into ML models: This topic covers building and training models. It also focuses on opting for suitable hardware for training.
Topic 3
  • Serving and scaling models: This section deals with Batch and online inference, using frameworks such as XGBoost, and managing features using VertexAI.
Topic 4
  • Automating and orchestrating ML pipelines: This topic focuses on developing end-to-end ML pipelines, automation of model retraining, and lastly tracking and auditing metadata.
Topic 5
  • Architecting low-code AI solutions: This section of the exam measures the skills of Google Machine Learning Engineers and covers developing machine learning models using BigQuery ML. It includes selecting appropriate models for business problems, such as linear and binary classification, regression, time series, matrix factorization, boosted trees, and autoencoders. Additionally, it involves feature engineering or selection and generating predictions using BigQuery ML.

Reference: https://cloud.google.com/certification/guides/machine-learning-engineer

Exam Details

The Google Professional Machine Learning Engineer exam is two hours long. The candidates can expect multiple-choice as well as multiple-select questions in their delivery of the certification test. The exam is currently given to the learners in the English language. To register for and schedule it, you need to pay $200 (plus applicable taxes). While registering for the test, the potential applicants will be offered to select the convenient mode of exam delivery: an online proctored session from a remote location or an in-person proctored session at the nearest testing center.

Preparation Process

The candidates for the Google Professional Machine Learning Engineer certification can find everything they need to efficiently prepare for the qualifying test on the official website. The most recommended resource offered by the vendor is the Machine Learning Engineer learning path. It contains both lessons and practical labs for a comprehensive understanding of the exam content. Moreover, the students can take advantage of the sample questions designed to help the potential test takers familiarize themselves with the possible exam questions. Finally, the applicants can opt for the Machine Learning Engineer Prep Webinar to join the Google experts and recently certified professionals for the tips and insights on the Machine Learning models, data processing systems, solution quality, and more.

How to book the Professional Machine Learning Engineer - Google

To apply for the Professional Machine Learning Engineer - Google, You have to follow these steps:

  • Step 1: Go to the Google Official Site
  • Step 2: Read the instruction carefully
  • Step 3: Follow the given steps
  • Step 4: Apply for the Professional Machine Learning Engineer Exam

Google Professional-Machine-Learning-Engineer Exam Overview:

Certification Vendor:Google Cloud
Exam Name:Google Cloud Professional Machine Learning Engineer Certification Exam
Exam Number:Professional-Machine-Learning-Engineer
Exam Format:Multiple choice, Multiple select, Case study
Available Languages:English, Japanese
Exam Duration:120 minutes
Certificate Validity Period:2 years
Related Certifications:Google Cloud Associate Cloud Engineer
Google Cloud Professional Data Engineer
Google Cloud Professional Cloud Architect
Real Exam Qty:Approximately 50–60 questions
Exam Price:$200 USD
Recommended Training:Vertex AI Documentation
Google Cloud Skills Boost - Machine Learning Engineer Path
Exam Registration:Google Cloud Certification Portal
Kryterion Webassessor
Sample Questions:Google Professional-Machine-Learning-Engineer Sample Questions
Exam Way:Online proctored exam or in-person testing via Kryterion test centers.
Pre Condition:No formal prerequisites required, but 3+ years of industry experience in ML/AI and familiarity with Google Cloud Platform are strongly recommended.
Official Syllabus URL:https://cloud.google.com/certification/machine-learning-engineer

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