The Learning Path

Learn AI, in order

29 lessons from “what is AI” to building agentic systems. Follow the path top to bottom — each one builds on the last.

0 of 29 lessons complete

Start here

What is AI? A Simple Guide for Complete Beginners

Module 1 · Foundations

1

Foundations

0/2

What AI actually is, before anyone sells you anything.

  1. 1

    What is AI? A Simple Guide for Complete Beginners

    BeginnerAI Basics5 min read
  2. 2

    ChatGPT vs Claude vs Gemini — Which One Should You Use?

    BeginnerTools8 min read
2

Math Foundations

0/4

The actual math behind training and inference — not hand-waving.

  1. 3

    Vectors, Matrices, and the Dot Product

    BeginnerMath9 min read
  2. 4

    Derivatives, Gradients, and the Chain Rule

    BeginnerMath8 min read
  3. 5

    Probability, Softmax, and Cross-Entropy

    BeginnerMath8 min read
  4. 6

    Gradient Descent: How Models Actually Learn

    IntermediateMath9 min read
3

Classical Machine Learning

0/4

Before deep learning — the models that still run most of the world's software.

  1. 7

    Linear & Logistic Regression: The Simplest Models That Actually Work

    BeginnerClassical ML8 min read
  2. 8

    Decision Trees, Random Forests, and SVMs

    IntermediateClassical ML8 min read
  3. 9

    K-Means and PCA: Finding Structure Without Labels

    IntermediateClassical ML7 min read
  4. 10

    Overfitting, Regularization, and the Bias-Variance Tradeoff

    IntermediateClassical ML8 min read
4

Deep Learning

0/4

From a single perceptron to the building blocks every modern network shares.

  1. 11

    Perceptrons to Multi-Layer Networks

    IntermediateDeep Learning7 min read
  2. 12

    Activation Functions: Why Networks Need Non-Linearity

    IntermediateDeep Learning6 min read
  3. 13

    Backpropagation, Normalization, and Dropout

    IntermediateDeep Learning8 min read
  4. 14

    Embeddings: Turning Anything Into a Vector

    IntermediateDeep Learning7 min read
5

Sequence Models

0/2

What came before attention, and the exact problem it was invented to fix.

  1. 15

    RNNs, LSTMs, and GRUs: How Models Used to Handle Sequences

    IntermediateSequence Models8 min read
  2. 16

    Encoder-Decoder Models and the Bottleneck That Started It All

    IntermediateSequence Models7 min read
6

Core AI

0/5

How the models underneath everything actually work.

  1. 17

    Attention & Transformers: The Idea Behind Every Modern AI Model

    IntermediateCore AI8 min read
  2. 18

    Parameters: What "a 70B Model" Actually Means

    IntermediateCore AI6 min read
  3. 19

    Mixture of Experts: How Models Get Bigger Without Getting Slower

    IntermediateCore AI7 min read
  4. 20

    Open Source vs Closed AI Models

    IntermediateCore AI7 min read
  5. 21

    GPUs: Why AI Needs Different Hardware Than Your Laptop

    IntermediateCore AI6 min read
7

Working With AI

0/3

Get consistently good output instead of generic mush.

  1. 22

    10 AI Prompts That Will 10x Your Productivity

    IntermediateHow-To4 min read
  2. 23

    AI for Students: How to Study Smarter, Not Harder

    BeginnerEducation7 min read
  3. 24

    How to Use AI to Automate Your Small Business

    All LevelsBusiness6 min read
8

Building With AI

0/1

Go from user to builder. No CS degree required.

  1. 25

    Building Your First AI App — A Step-by-Step Guide

    IntermediateTutorial12 min read
9

Agentic AI

0/4

The frontier — systems that act, not just answer.

  1. 26

    What Is an AI Agent? (And What It Isn’t)

    IntermediateAgentic AI7 min read
  2. 27

    How AI Agents Use Tools — The Loop That Powers Everything

    IntermediateAgentic AI8 min read
  3. 28

    What Is MCP? How Agents Plug Into the Real World

    IntermediateAgentic AI6 min read
  4. 29

    Should You Actually Build an Agent? A Decision Guide

    IntermediateAgentic AI7 min read