Google Professional Machine Learning Engineer (PMLE) – Tests
About this course
Are you ready to pass one of the most challenging and career-defining AI certifications on the market? The Google Professional Machine Learning Engineer (PMLE) exam is widely regarded as the toughest AI/ML certification available — and this course gives you exactly what you need to pass it on your first attempt.This course includes 5 full-length practice exams with 300 scenario-based questions meticulously crafted to mirror the actual PMLE exam experience. Every question is tied to a real exam domain, includes a detailed explanation, and is designed to expose the exact trade-offs and edge cases that trip up even experienced engineers on exam day.WHY THIS COURSE STANDS OUT:The PMLE exam is not a memorization test. It is a high-stakes, scenario-driven challenge that requires you to think like a senior ML engineer at Google. Our questions simulate exactly that. You will face multi-paragraph case studies requiring you to select the best Vertex AI architecture, choose between batch and online inference, decide when to use AutoML versus custom training, design CI/CD pipelines for ML models, evaluate bias and drift in production systems, and much more.WHAT IS COVERED:Domain 1 (13%): Architecting low-code AI solutions using BigQuery ML, AutoML, pre-built ML APIs, Model Garden, and RAG patterns with Vertex AI Agent Builder.Domain 2 (14%): Collaborating on data and models with Dataflow, TFX, BigQuery, Vertex AI Feature Store, Jupyter notebooks, and experiment tracking.Domain 3 (18%): Scaling prototypes to production ML models using Vertex AI custom training, Kubeflow Pipelines, hyperparameter tuning with Vertex AI Vizier, and distributed training on TPUs and GPUs.Domain 4 (20%): Serving and scaling ML models with online and batch inference, Vertex AI Endpoints, A/B testing, canary deployments, and hardware optimization for cost and latency.Domain 5 (22%): Autom
69/100
CourseAsk score
- What the provider tells you
- 45/45
- Who stands behind it
- 8/35
- How complete the listing is
- 16/20
Scores how much the provider publishes and who stands behind it — not how well it is taught.
What you'll learn
- understand low-code AI solutions using BigQuery ML and Vertex AI
- collaborate on data and models with tools like Dataflow and BigQuery
- scale prototypes to production ML models using Vertex AI and Kubeflow Pipelines
- serve and scale ML models effectively with online and batch inference strategies
- evaluate model performance and operationalize CI/CD pipelines for ML applications
Course objectives
- help students pass the PMLE exam on their first attempt
- simulate real exam conditions to prepare students effectively
- provide detailed feedback and explanations for practice questions
Price shown by Udemy — confirm on their site.
Enroll on UdemyYou'll be redirected to Udemy to complete enrollment.
- Listed & compared by CourseAsk
- English · 0
Compared on these lists
Where this course ranks against the alternatives.
Coursera