Resources for the Google Cloud Professional Machine Learning Engineer Certification

4 min. read

Recently I passed the Google Cloud Professional ML Engineer Certification Exam and received a few queries on how to prepare for the exam. Hence I am writing up a post to share some free/low-cost training offers and resources that have helped me pass the exam.

One thing to note is that I have previously completed the Google Cloud Professional Data Engineer Certification and have some prior experience with using Google Cloud Platform and TensorFlow/Keras before attempting this certification exam. I shall suggest some resources for learning the portions related to Data Engineering and TensorFlow if you are not familiar with them.

There are already some folks who have completed the certification exam and have kindly shared their experiences. These are the articles that I reference:

Article References

You should definitely check out the official guides and sample questions linked below.

Official References

Below are some free/low-cost training offers and books that I use for preparation or revision.

Courses/books that I used for preparation/revision

Additional resources

Below are some additional resources that I focused for the respective sections in the exam guide.

Please note that this should be read in tandem with Dmitri Lerko and Steven Macmanus’ guide mentioned above for a more comprehensive coverage/revision depending on your experience level/background.

Problem Framing

ML Solution Architecture

Data Preparation and Processing

ML Model Development

ML Pipeline Automation & Orchestration

System Biases, Fairness, Interpretability