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Applied LLMs — origins, evidence and applications

A readable route through LLM foundations, attention, retrieval, prompting, audio, clinical NLP, statistical learning and deployment responsibilities.

What you’ll work toward

  • Choose a route through foundations, mechanics and applications
  • Use prerequisite and exit tests for each branch
  • Distinguish source review, local execution and service deployment
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Before the first lesson

  • No calculus required; willingness to trace a small weighted sum

These are the starting lesson’s prerequisites, not requirements for every advanced topic below.

How to practise this subject

Attempt each lesson’s exercises before opening the explanation. Reconstruct its main example, change an assumption, and use the stated test boundaries to judge what you have actually checked.

  1. 01beginner · 22 min

    Where LLMs Came From, and What They Actually Are

    A source-grounded history of language modelling, five core mechanisms and the boundaries between a predictor and a deployed assistant.