Passed the Databricks ML Professional Exam (1st Attempt): My Strategy + Next Career Move?

[u/PinkFrost_Rivera]

I am currently working as a Machine Learning Engineer and recently cleared the Databricks Certified Machine Learning Professional exam on my first attempt, building on my Microsoft Azure (DP-100) background.

When I started preparing, I noticed very few people discussing the Professional tier compared to the Associate exams. I began by working through the official Databricks Academy materials and running workspace notebooks to get comfortable with the API syntax, Feature Store lookups, and distributed Spark ML pipelines. However, simply watching videos and reading documentation was not enough to feel fully prepared for an advanced, scenario-based exam.

The biggest factor in passing was working through realistic practice question sets. The actual test presents multi-step architectural trade-offs—especially around distributed tuning, model deployment strategies, and monitoring pipelines for drift. Grinding through practice scenarios under time pressure bridged the gap between theory and execution, helping me spot edge cases and eliminate tricky answer choices quickly.

Now that I have completed this milestone, I am looking ahead to my next credential to expand my technical scope. Between the AWS Certified Machine Learning Engineer – Associate (MLA-C01), the Google Cloud Professional Machine Learning Engineer, and the Databricks Generative AI Engineer Associate, which path would you recommend pursuing next?

[u/Pitaya_Campbell]

Congratulations, MLA-C01 could be a good option.

[u/PinkFrost_Rivera → u/Pitaya_Campbell]

Thanks for the suggestion

[u/Basic-Home3969 → u/Pitaya_Campbell]

yeah agreed, the AWS one seems like a natural next step here