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Master production-grade ML on Google Cloud with Vertex AI, BigQuery ML, and MLOps. The exam tests real-world skills across the full ML lifecycle.
Practice with 300 curated scenario-based questions covering Vertex AI, BigQuery ML, pipelines, monitoring, and more.
Interactive flashcards for Vertex AI services, ML design patterns, drift types, pipeline components, and responsible AI concepts.
Simulate the real 2-hour PMLE exam with timed 60-question practice tests and detailed performance analytics by domain.
In-depth notes covering all 6 exam domains: BigQuery ML, Vertex AI, distributed training, model serving, pipelines, and monitoring.
Curated official Google Cloud documentation, Skills Boost learning paths, and ML design pattern resources.
Structured 6-week study plan with domain-specific weekly goals, time estimates, and exam-day strategies.
View your domain-by-domain performance, strengths, and areas to improve on your path to PMLE certification.
2 hours
~60 questions
~70% (Google does not publish exact score)
Multiple choice, multiple select, scenario-based
$200 USD
2 years
BigQuery ML, AutoML, pre-built APIs
Data validation, responsible AI, model cards
Custom training, distributed training, HPT
Vertex AI Endpoints, batch prediction, optimization
Vertex AI Pipelines, CI/CD for ML, Feature Store
Drift detection, model monitoring, retraining
120 minutes
~60 questions
See official exam guide
Professional ML Engineer
Google Cloud
BigQuery ML, Vertex AI AutoML, Pre-built APIs
TFDV, Vertex Explainable AI, Model cards
Custom Training, Distributed Training, Hyperparameter Tuning
Vertex AI Endpoints, Online Prediction, Batch Prediction
Vertex AI Pipelines, KFP SDK, Feature Store
Model Monitoring, Drift Detection, Retraining Triggers
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