Micro Free Course — 100% Free Learning
All lessons in this module are free to learn. Sign in with Google to save your progress.
LLM Foundations: What They Actually Are
What LLMs are (and aren't); tokens, embeddings, and the transformer in plain language; the pretraining/fine-tuning/prompting spectrum; the 2026 model landscape (closed vs open, sizes, costs); context windows.
Module Content
What LLMs Are (and What They Aren't)
A practical definition. LLMs predict the next token; everything else is engineering on top of that. FIND_VIDEO: search 'what is a large language model how it works' — recommended channel: 3Blue1Brown / Andrej Karpathy. Aim for 11 min or under.
Quiz: Tokens, Embeddings & Transformers
The minimum mental model. Skip the math; get the intuition that makes everything downstream easier.
The Pretraining vs Fine-tuning vs Prompting Spectrum
Three ways to get an LLM to do what you want. Most teams pick the wrong one first. FIND_VIDEO: search 'LLM pretraining fine-tuning prompting comparison' — recommended channel: Andrej Karpathy / DeepLearning.AI. Aim for 10 min or under.
Quiz: Adaptation Strategies & LoRA
Pretrain, fine-tune, RAG, or just prompt? Each has different cost, complexity, and effectiveness. Pick deliberately.
How to Compare Models — Closed vs Open, Size, Cost
The 2026 model landscape. Closed (Claude, GPT, Gemini), open (Llama, Mistral, Qwen) — which to pick when. FIND_VIDEO: search 'claude vs gpt vs llama comparison 2026' — recommended channel: AI Engineer / Trelis Research. Aim for 11 min or under.
Quiz: Frontier Models & Cost Selection
Closed vs open, sizes, capabilities, costs. Pick by your task and constraints, not by marketing.
SUBMISSION: Case 1 — Multi-Model Evaluation on Ticket Classification
Compare Claude Sonnet vs GPT-4o-mini vs Llama 70B on a real classification task. Build the eval, run it, decide.
Tokens, Context Windows, and Why They Matter
The fundamental constraint that shapes every LLM application: tokens in, tokens out, with a hard limit. FIND_VIDEO: search 'LLM context window tokens lost in middle' — recommended channel: AI Engineer / Greg Kamradt. Aim for 10 min or under.
Quiz: Token Economics & Context Windows
Tokens cost money and time. Manage them deliberately; production-grade LLM apps live and die by their token discipline.