datarekha

ML Engineer

Build, train, and deploy models — the role most teams actually need.

12–18 weeks Intermediate → Advanced 120 lessons

Curriculum

  1. 1

    Python

    40 lessons

    From syntax to production AI apps — the language for everything.

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  2. 2

    NumPy

    14 lessons

    The numeric foundation of the entire data stack.

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  3. 3

    Pandas

    13 lessons

    The de-facto tool for tabular data in Python.

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  4. 4

    Math for ML

    16 lessons

    Linear algebra, calculus, and probability with code.

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  5. 5

    Machine Learning

    14 lessons

    Trees beat neural nets on most tabular problems — and other truths.

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  6. 6

    Deep Learning

    13 lessons

    PyTorch-first, transformer-heavy, no fluff.

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  7. 7

    MLOps

    10 lessons

    Ship models, not notebooks.

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