How Transformer LLMs Work
by DeepLearning.AI
A visual, code-backed tour of the modern transformer LLM, component by component.
Overview
Taught with Jay Alammar and Maarten Grootendorst (authors of 'Hands-On Large Language Models'), this course walks through the recent transformer architecture as used in today's LLMs: tokenization and embeddings, the attention mechanism and its efficient variants, the transformer block, and how tokens are generated one at a time. It bridges the conceptual illustrated explainers and real code.
At a Glance
- Topic
- Models
- Level
- Intermediate
- Format
- Course
- Cost
- Free
- Duration
- ~1-2 hours
- Provider
- DeepLearning.AI
- Hands-on
- Yes — code/exercises
- Certificate
- None
What You’ll Learn
- ✓Tokenization and embeddings in modern LLMs
- ✓The attention mechanism and recent variants
- ✓Inside the transformer block
- ✓How text is generated token by token
Highlights
- •Taught by the author of The Illustrated Transformer
- •Concept plus code
Who It’s For
Best For
- ✓Learners moving from intuition to mechanics
Prerequisites
- •Basic Python
- •Neural network basics
FAQ
What is How Transformer LLMs Work?
A short course dissecting the components of a modern transformer LLM — tokenization, attention, and the generation loop.
Is How Transformer LLMs Work free?
How Transformer LLMs Work is free to access.
What level is How Transformer LLMs Work for?
How Transformer LLMs Work is aimed at a intermediate audience. Recommended background: Basic Python, Neural network basics.
How long does How Transformer LLMs Work take?
Expect roughly ~1-2 hours. Most learners work through it at their own pace.
What will I learn from How Transformer LLMs Work?
You'll learn: Tokenization and embeddings in modern LLMs; The attention mechanism and recent variants; Inside the transformer block; How text is generated token by token.