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:
- Frame ML problems
- Architect ML solutions
- Prepare and process data
- Develop ML models
- Automate & orchestrate ML pipelines
- Monitor, optimize, and maintain ML solutions
If you are interested in obtaining this certification, this is the learning path recommended by Google to prepare for the exam:
Additionally, we recommend the following trainings as part of your readiness journey: