MLOps and LLMOps

Stage 1 · Lesson 5 of 8

Config and secrets outside the code

From notebook to package

is anything that changes between runs or environments: data paths, (settings chosen before training), model names, prompt versions, thresholds. Keep it in a versioned file such as params.yaml so a run can record exactly which values it used.

Secrets, such as keys and database passwords, never go in files in Git: read them from environment variables locally and from a secrets manager in the cloud. With this split the same code trains on a 5 percent sample in CI and on full data in production, and changing a threshold is a reviewed config change rather than a code edit.

Common trapan API key in a notebook cell or a committed .env file, which leaks the first time the repository is shared.

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Resources for this stage

Start with· follow one of these

  • CoursePaid
    Grokking Python Fundamentals

    Design Gurus · Beginner · $50

    If your Python stops at notebooks: modules, functions, classes and error handling done properly

  • CourseFree
    Made With ML

    Goku Mohandas · Advanced

    Free: the scripting, CLI, testing and documentation lessons turn notebook code into a real project

Practise

  • Free exercises that make you build, run and debug images until Dockerfiles feel routine

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