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Preparation Guide for Professional Machine Learning Engineer - Google
Introduction for Professional Machine Learning Engineer - Google
A Professional Machine Learning Engineer designs, builds, and productionizes ML models to solve business challenges using Google Cloud technologies and knowledge of proven ML models and techniques. The ML Engineer is proficient in all aspects of model architecture, data pipeline interaction, and metrics interpretation and needs familiarity with application development, infrastructure management, data engineering, and security.
The Professional Machine Learning Engineer exam assesses your ability to:
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Reference: https://cloud.google.com/certification/guides/machine-learning-engineer
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| Section | Weight | Objectives |
|---|---|---|
| Train and deploy models | 20% | - Use Vertex AI deployment features and infrastructure - Implement generative AI deployment patterns - Deploy models for online, batch, and streaming prediction - Configure training jobs and environments |
| Monitor and optimize AI solutions | 16% | - Monitor data quality and pipeline health - Optimize cost, latency, and resource usage - Monitor model performance, fairness, and drift - Troubleshoot and maintain production systems |
| Architect low-code AI solutions | 12% | - Identify use cases for low-code/no-code AI tools - Apply responsible AI principles to low-code designs - Design solutions using Vertex AI Studio, Model Garden, and Agent Builder |
| Collaborate to manage data and models | 16% | - Organize and prepare enterprise data
- Manage datasets and features in Vertex AI |
| Scale prototypes into AI models | 18% | - Work with foundation models and generative AI techniques - Optimize model performance and generalization - Select appropriate model architectures and frameworks - Design and run experiments |
| Automate and orchestrate ML pipelines | 18% | - Implement CI/CD for ML systems - Use Vertex AI Pipelines, TFX, and other orchestration tools - Design end-to-end ML workflows - Automate retraining and model updates |
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