Modern AI is not magic.
Nearly everyone uses AI now. Far fewer can say what happens between typing a question and reading an answer.
That gap is where the surprises come from: the confident wrong answer, the detail it forgot, the tool it ran that you never asked for.
This interactive course takes the whole thing apart. How models are trained, how they write a response one token at a time, and how the products around them use memory, retrieval, tools, and agents; starting from zero and going as deep as you'd like.
- Transformers
- RAG
- Tokens
- Embeddings
- Tool calling
- Training data
- Next-token prediction
- Agents
- MCP
- Memory
Outline*
1.AI Basics
2.AI Products
3.AI Usage
4.Components of an LLM
5.How Models Learn
6.Coding with LLMs
7.Inside a Transformer Layer
8.Producing the Next Token
9.Fine-tuning and RLHF
*This course’s contents are subject to change
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