Learn · Pathway
How an LLM works, end to end
The flagship journey — from raw text to a grounded answer. Interactive demos interleaved with the best explainer videos, in learning order.
- 1 Token Visualiser Interactive demo
- 2 Video · IBM Technology
- 3 Embeddings Explained Interactive demo
- 4 Video · StatQuest
- 5 Attention, Visualised Interactive demo
- 6 Video · 3Blue1Brown
- 7 Positional Encodings Interactive demo
- 8 Causal Self-Attention Interactive demo
- 9 Autoregressive Generation Interactive demo
- 10 Temperature & Sampling Interactive demo
- 11 Beam Search vs Greedy Interactive demo
- 12 Cross-Attention Interactive demo
- 13 The KV Cache Interactive demo
- 14 Video · 3Blue1Brown
- 15 Context Windows & Chunking Interactive demo
- 16 How RAG Works Interactive demo
- 17 Video · IBM Technology
Other pathways
AI for the curious
9 stepsNo maths degree required. A gentle, visual path from “what is a neural network?” to how modern AI writes and reasons.
See pathway →For decision-makers
8 stepsThe concepts behind responsible enterprise AI — what LLMs and RAG are, where bias and fraud trade-offs bite, and how to size up your own adoption.
See pathway →Responsible & safe AI
7 stepsbigspark's specialism, made hands-on. Why safety matters, then the real enterprise trade-offs — prompt-injection guardrails, bias and fairness, fraud thresholds — and the alignment ideas behind them.
See pathway →Classic ML foundations
8 stepsBefore the transformers — the workhorse algorithms every data scientist knows, hands-on: regression, classification, clustering and learning by gradient descent.
See pathway →