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Deep Understanding of AI Large Language Models

Updated
17 Sept 2026
1 min read
2 sections
Page 1 of 32
Deep Understanding of AI Large Language Models

Join us on a deep dive into the architecture, mathematics, and implementation of modern Large Language Models (LLMs). This series breaks down complex concepts into digestible modules, starting from the very basics of how machines process text.

Adapted from A deep understanding of AI language model mechanisms — https://udemy.com/course/dullms_x

Course Modules

  • Token Embedding — /blog/ai-llms/token-embeddings

What We'll Cover

  • Tokens & Embeddings: How text is transformed into high-dimensional vectors.
  • Attention Mechanisms: The "Self-Attention" magic that powers Transformers.
  • Transformer Architecture: Building the encoder and decoder from scratch.
  • Training & Fine-tuning: From pre-training on the web to instruction tuning.
  • Inference & Optimization: Making LLMs fast and efficient.

In this section

  1. [01]Inside the Tokenizer18 pages
  2. [02]Word Embeddings11 pages