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Learning Path

Developer to AI Engineer

The complete roadmap for software developers transitioning into AI engineering roles.

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  1. 1

    Python for AI Engineering

    Python Foundations for AI Engineering

    60 pages
    BeginnerPython

    Everything a working developer needs in Python for AI: environments, NumPy, data pipelines, notebook workflows and the libraries the AI stack actually uses.

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  2. 2

    Large Language Models

    LLM Fundamentals: Tokens to Alignment

    50 pages
    IntermediateLarge Language Models

    How large language models really work: tokenisation, pretraining objectives, instruction tuning, RLHF and decoding strategies, explained visually.

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  3. 3

    Transformers and Attention

    Transformer Architecture, Explained by Hand

    42 pages
    IntermediateTransformers

    The transformer block, self-attention and multi-head attention drawn and annotated page by page — the clearest way to internalise the architecture behind modern LLMs.

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