🎓 Learn
One map,
from zero to the frontier
8 levels, 145 articles. Each labeled by difficulty (🥚🐣🐥).
Read in order, or jump to whatever interests you.
🥚
L0
AI Primer
For everyone
12 lessons
- 01 🥚 12 minAI, ML, DL, LLM — How Are They Related?The four most confused terms in tech today. After this article, no buzzword salad can fool you again.
- 02 🥚 15 minAI History in 15 Minutes: From Turing to ChatGPT70 years compressed into 11 moments. Not a timeline — only the events that changed the game.
- 03 🥚 14 minWhat AI Can and Can't Do — Talking With ReceiptsStop listening to hype and FUD. Item by item: what AI already beats you at, and what it absolutely can't do yet.
- 04 🥚 13 minWhat Is "Hallucination"? Why It Happens, How to MitigateWhy does AI confidently make stuff up? It's not a bug—it's how this kind of AI works. Understand the mechanism, you'll know how to use it.
- 05 🥚 12 minPrompt Engineering Basics: 10 Moves to Make AI 10× More PreciseNo jargon, no fluff. 10 actions, 20 minutes to master. This article alone puts you ahead of 80% of AI users.
- 06 🥚 10 minWhat Is "Intelligence", Really?A word we thought was clear—but never actually defined. The next time you debate "is AI really intelligent," read this first.
- 07 🥚 8 minYour First AI Chat in 5 MinutesTheory's done. Hands-on now. Step-by-step signup, login, and what to say first.
- 08 🥚 12 minWill AI Take My Job? A Framework, Not DoomStop asking "will AI replace me." Start asking "which parts of my job will AI replace?" This framework will serve you for a lifetime.
- 09 🥚 11 minChatGPT vs Claude vs Gemini: An Unbiased ComparisonNo hype, no FUD. The real differences between the top 3 LLMs—so you can pick the right one for what you actually do.
- 10 🥚 10 minAI Data Safety: Where Do Your Chats Go?The contracts, medical records, company secrets you paste into ChatGPT—how are they handled? Who can see them? Once you know, you can use AI with confidence.
- 11 🥚 14 minAI Glossary: 30 Terms for Non-Technical ReadersToken, Embedding, Transformer, RAG, Fine-tuning… the jargon flying around chats. Here's the cheat sheet.
- 12 🥚 8 minL0 Graduation: What's Next?You finished the primer path. This article helps you choose what to learn next—go deeper, go wider, or just build something.
🐣
L1
Math & Python
Minimal prerequisites
4 lessons
- 01 🐣 8 minMath Without Fear: This Is Supposed to Be a Math Class, But Let's Try a Different WayScarred by high school math? It's not your fault. It's the textbook. Here we use diagrams, animations, and Python to make AI math actually make sense.
- 02 🐣 14 minLinear Algebra: Vectors and Matrices via Pictures and PositionsAll of AI is matrix operations under the hood. This one doesn't teach determinants or eigenvalues—just lets you "see" what vectors are doing.
- 03 🐣 13 minDerivatives and Gradients: The Math Definition of "Learning"The essence of "training a neural network" is derivatives. Once you understand this word, AI training stops being mysterious.
- 04 🐣 12 minProbability and Maximum Likelihood: Why ML Is a Probability ProblemAll ML models are actually doing one thing: finding parameters that maximize the probability of seeing the data. Once this clicks, all of ML becomes transparent.
🐥
L2
Classical ML
Foundations
4 lessons
- 01 🐣 11 minSupervised / Unsupervised / Reinforcement: The Three Worldviews of MLEvery ML algorithm belongs to one of these three. Understand the taxonomy, and any new algorithm finds its home.
- 02 🐣 11 minLinear Regression: The Simplest and Most Profound ML ModelThink linear regression is too simple? It's the last layer of every neural network, the starting point of every ML project, and still beats deep learning in many scenarios.
- 04 🐣 11 minDecision Trees: The Most Interpretable ML AlgorithmA chain of yes/no questions forms a tree of decisions. It's the foundation for XGBoost and LightGBM—the champions of Kaggle.
- 05 🐣 13 minRandom Forest + Boosting: From Weak Learners to SuperhumanA single tree is mediocre. A crowd of trees voting is supernatural. The origin story of XGBoost—the Kaggle champion for a decade.
🧠
L3
Deep Learning
Including Transformer
2 lessons
- 05 🐣 18 minAttention Explained: From Intuition to Complete DerivationAttention is all you need. This article takes you from "what is it actually doing" to "every line of its formula"—the core of Transformer, fully digested.
- 06 🐣 15 minCNN Convolution Principles: From Filters to ResNetBefore Transformer dominated, CNN ruled computer vision. Today it remains the default for image processing. This article explains "convolution" clearly.
🦅
L4
LLM & Generative
The frontier
3 lessons
- 01 🐣 16 minHow LLMs Are Trained: Pretrain → SFT → RLHF, the Full PipelineTraining an LLM isn't one step—it's three completely different stages. Each uses different data, different objectives. After this, you can talk to ML engineers.
- 03 🐣 17 minRAG from 0 to 1: Let LLMs Answer Based on Your DataEnterprise AI applications are 90% RAG. This article walks you through building a runnable RAG system—from chunking to deployment.
- 07 🐣 11 minMCP Protocol Explained: The USB of the AI WorldAnthropic launched MCP in 2024 — letting any tool plug into any LLM. In one year it became the de facto standard for AI Agent ecosystems.
🎨
L5
Multimodal
Diffusion / Video / 3D
3 lessons
- 01 🐣 13 minMultimodal Overview: How AI "Sees, Hears, and Reads" at OnceGPT-4o recognizes your sketch, Sora generates video—how does "multimodal" AI work? This article opens the panoramic view.
- 02 🐥 15 minDiffusion Math: From Adding Noise to GenerationStable Diffusion, DALL·E 3, Sora all use diffusion models. This article explains the core math—with minimal formulas.
- 03 🐣 13 minViT and CLIP: Teaching Transformers to SeeSlice images into patches, feed to Transformer—the biggest paradigm shift in computer vision in 2020.
🛡️
L6
Safety & Alignment
Critical topics
2 lessons
- 01 🐣 12 minWhy AI Alignment: From Right/Wrong to ValuesThe more capable an AI, the more critical alignment becomes. This article clarifies what "alignment" really means and why it's one of the most important AI research directions.
- 02 🐥 12 minRLHF vs Constitutional AI: Two Mainstream Alignment Methods ComparedOpenAI uses RLHF; Anthropic uses CAI. Both make LLMs "listen", but with completely different philosophies.
⚙️
L7
Systems & Eng
Production
1 lessons