Become a Google Certified Professional Machine Learning Engineer

Google Certified Professional Machine Learning Engineer

A Professional Machine Learning Engineer designs, builds, and produces 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 should be familiar with application development, infrastructure management, data engineering, and security.

Abilities validated by the certification

  • Ability to frame ML problems
  • Ability to architect ML solutions
  • Ability to prepare and process data
  • Ability to develop ML models
  • Ability to automate & orchestrate ML pipelines
  • Ability to monitor, optimize, and maintain ML solutions

Recommended experience

3+ years of industry experience, including 1+ years of designing and managing solutions on GCP.

Prepare for the exam

0. Practice

Before you attempt the exam, hands-on experience with Google Cloud products and solutions is recommended. You can build free products herehttps://cloud.google.com/free.

1. Exam guide

You can review the exam guide herehttps://cloud.google.com/certification/guides/machine-learning-engineer.

2. Training

You can view the preferred learning path here https://cloud.google.com/training/machinelearning-ai#data-scientist-learning-path.

3. Webinar

You can attend a webinar by registering herehttps://cloud.google.com/certification/machine-learning-engineer/.

4. Additional resources

You can view the additional resources on the concepts and critical components of GCP by visiting:

5. Sample questions

You can view the sample questions for this certification here.

6. Schedule your exam

You can register for your exam here.

Free Resources

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