Build, deploy, automate and monitor ML and generative AI solutions on Google Cloud.
4.7(247 reviews)
The Google Cloud Professional Machine Learning Engineer exam checks that you can take machine
4.7 out of 5 from 247 reviews
Moderate difficulty overall. The review covered training-serving skew, hyperparameter tuning, and monitoring, and the scenario questions were specific without feeling repetitive.
Useful for checking weak spots in BigQuery ML, pipelines, and explainability. A few items were straightforward, but others needed careful reading and a second pass.
I liked the mix of TensorFlow model tuning, data validation, and MLOps questions. Some sections pushed me to think through error analysis instead of just picking the obvious answer.
Clear focus on feature engineering, model evaluation, and Vertex AI workflows. The tasks around preprocessing and deployment felt practical, though a few prompts were worded more densely than expected.
No. We write original exam-style practice questions that cover the same sections and skills as the official exam guide. We don't sell copies of real exam questions.
50 to 60 multiple choice and multiple select questions in two hours, taken online with a remote proctor or at a test center.
Google does not publish a passing score. You get a pass or fail result.
Two years.
Take a test, read the explanation for every question you miss, and learn when Google points you to a pre-trained API, AutoML or custom training, since many questions turn on that choice.