If you've spent any time looking at AI and machine learning certifications, you've probably noticed the same thing I did: every cloud vendor has its own, they all use different vocabulary, and none of them tell you how their cert maps to anyone else's. For a developer trying to decide where to invest study time, that fragmentation is the real obstacle — not the difficulty of the material.
I'm Larry Dale, founder of PowerKram (https://powerkram.com), where I build scenario-based learning systems for people moving into cloud and AI roles. After helping a lot of developers prep across vendors, I've come to believe the certifications are far more alike than the marketing suggests. Once you see the shared skeleton, picking a path gets a lot easier.
This post is the mental map I give developers who are staring at a wall of AWS, Azure, Google Cloud, DataBricks, and Salesforce AI certs and don't know where to start.
The Vendors Disagree on Words, Not Concepts
Each cloud provider brands its AI track differently, but underneath, they're testing the same handful of competencies. Strip away the product names and almost every cloud AI certification is checking whether you can:
