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A skippable 'path' that functions as a glorified glossary for Azure ML deployment terms. It’s too brief and abstract to teach anything practical.
Decision summary
2.8/5 Last verified: August 31, 2026
Data scientists who need a quick, text-based overview of what Azure deployment endpoints are.
The 'exercise' is just reading and doesn't involve actually running any code.
Data scientists who need a quick, text-based overview of what Azure deployment endpoints are.
Anyone looking for a hands-on lab or a tutorial that actually builds and deploys something from scratch.
This entire 'path' took less time than it took for my Azure trial to provision the first time. I wanted to get a small, guided project for deploying a model, since that's a big gap in my skillset. The title says 'Deploy and consume models', but what it really means is 'Read about deploying and consuming models'. There is no code to write, no model to train, and no endpoint to actually create or test.
The exercise sections are just instructions on where you *would* click in the Azure ML Studio if you *were* deploying a model. They give you a pre-packaged GitHub repo with all the finished files, and the steps are literally 'Go look at this YAML file' and 'Go look at this Python script'. It's like a museum tour of a deployment process. I didn't touch my keyboard for anything other than scrolling.
I guess I learned the difference between a managed online endpoint and a batch endpoint, but I could have gotten that from the first paragraph of the official documentation. For something that is supposed to be part of the DP-100 exam prep, it feels shockingly hollow. It provides the vocabulary but none of the muscle memory. The linked DP-100 path seems to have the real labs; this just felt like the promotional trailer for it.
Last verified: August 31, 2026. We re-check course details periodically — see our methodology. Pricing and availability can change; always confirm on the official site.
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