I took me over 4 months to nail this exam as I started from ground „Zero” 🙂 The exam is 2h with 60 questions. The exam guide can be found here: https://cloud.google.com/certification/machine-learning-engineer together with recommended materials.

I suggest you take the following path:

Make sure you are at the PCA level with strong K8s background.

1. Start with 101 Google ML Crash course (40h)

https://developers.google.com/machine-learning/crash-course

2. Watch all the AI Adventures videos (20h)

3. Redo the with 101 Google ML Crash course (10h)

4. Go through the ML Coursera/PluralSights training

https://www.pluralsight.com/paths/machine-learning-on-google-cloud-platform

5. Read carefully the docs for Tensorflow Extended (4h)

https://www.tensorflow.org/tfx/

6. Watch carefully the TFX video series (4h)

7. Do the MLOPs trainig https://www.coursera.org/learn/mlops-fundamentals/ (15h)

8. Watch carefully the Kubeflow series (4h)

10. Read carefully the AI Platform docs https://cloud.google.com/ai-platform (5h)

11. Do as many Qwiklabs for Kubeflow/TFX as possible (20h)

12. I recommend you watch the series on ML by Luis Serrano (20h)

https://www.youtube.com/channel/UCgBncpylJ1kiVaPyP-PZauQ

It is very much 101 on ML and covers the same material as the Crash Course but is easier to comprehend.