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LEARNPATH

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AI Engineer / MLOps basics

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AI Engineer

01Python syntax & types
02Lists, dicts, sets
03Linear algebra intuition
04Probability & statistics
05SQL fundamentals
06Data wrangling
07Machine learning fundamentals
08Neural networks
09PyTorch basics
10Evaluation & metrics
11MLOps basics
12Containers & orchestration
13AI ethics & responsibility

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Stage 04 · 04 · Production · skill 2 of 3

MLOps basics

Version data and models. A notebook is not a production system.

Recommended first: Machine learning fundamentals

After this you will be able to

Describe the difference between experiment and production
Name what you would log for a training run
Sketch a simple training → eval → deploy pipeline

Open MLOps: Continuous delivery and automation practices

Google Cloud · why we picked it

Previous Next: Containers & orchestration

Practice

No playground attached to this skill. The practice lab has every runtime.

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