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Learn AI, from zero.
A complete AI course for everyone — no coding, no maths degree, no jargon. From “what is AI?” to agents, prompts, and real business use. Short lessons, everyday examples, and a quiz at the end of each one.
- Free always, all of it
- Plain English no jargon, no maths
- Every lesson ends with a quiz
Learn AI — the full curriculum
11 modules, 159 lessons, zero jargon. Start at module one and go in order, or jump to what you need. Every lesson is written in very simple English — with examples, a memory trick, a glossary, and a quiz. Open a lesson and our AI teacher prepares it for you; after that it loads instantly for everyone.
new · added weekly by our AI Fresh lessons One new lesson every week, picked from what is happening in AI right now.
module 1 · beginner The Basics Start here. What AI is, in plain words.
- 01What is AI?
- 02What is NOT AI (common confusion)
- 03A short history of AI
- 04What is data?
- 05What is an algorithm?
- 06What is a model?
- 07How is a computer different from a human brain?
- 08Narrow AI, General AI, and Super AI
- 09AI vs Machine Learning vs Deep Learning vs Data Science
- 10How does an AI actually learn? (training explained)
- 11Where do you already use AI every day?
- 12Can AI think and feel? (the honest answer)
module 2 · beginner Machine Learning Basics How machines learn from examples.
- 13What is Machine Learning?
- 14Supervised learning (learning with an answer key)
- 15Unsupervised learning (finding patterns alone)
- 16Reinforcement learning (learning by reward)
- 17Self-supervised learning
- 18Features and labels
- 19Training data, validation data, test data
- 20What is a prediction?
- 21Classification vs Regression
- 22Overfitting and underfitting
- 23What is model accuracy?
- 24Precision, recall, and F1 score
- 25The confusion matrix
- 26What is a loss function?
- 27Gradient descent (how a model improves)
- 28Learning rate, epochs, and batch size
- 29Hyperparameters vs parameters
- 30Cross-validation
module 3 · beginner to intermediate Classic AI Algorithms The workhorses used in real business every day.
- 31Linear regression
- 32Logistic regression
- 33Decision trees
- 34Random forest
- 35K-Nearest Neighbours (KNN)
- 36Support Vector Machines (SVM)
- 37Naive Bayes
- 38K-means clustering
- 39Dimensionality reduction and PCA
- 40Gradient boosting (XGBoost, LightGBM)
- 41Ensemble learning (many models together)
- 42Anomaly detection (finding the odd one out)
- 43Time series forecasting
- 44Recommendation systems
module 4 · intermediate Neural Networks and Deep Learning The engine behind modern AI.
- 45What is a neural network?
- 46The neuron (perceptron)
- 47Layers: input, hidden, output
- 48Weights and biases
- 49Activation functions
- 50Forward propagation
- 51Backpropagation (how it corrects mistakes)
- 52Why deep learning needs so much data
- 53Convolutional Neural Networks (CNN) — for images
- 54Recurrent Neural Networks (RNN) — for sequences
- 55LSTM and GRU
- 56What is a Transformer?
- 57The attention mechanism
- 58Embeddings (turning words into numbers)
- 59Transfer learning
- 60Fine-tuning a model
- 61Autoencoders
- 62GANs (two AIs competing)
- 63Diffusion models (how AI draws pictures)
module 5 · beginner to intermediate Generative AI and LLMs ChatGPT, prompts, and the tools everyone talks about.
- 64What is Generative AI?
- 65What is a Large Language Model (LLM)?
- 66How does ChatGPT actually work?
- 67Tokens and tokenization
- 68The context window (AI memory limit)
- 69Temperature, top-p, and randomness
- 70Why AI sometimes makes things up (hallucination)
- 71What is prompt engineering?
- 72Zero-shot, one-shot, and few-shot prompting
- 73Chain-of-thought prompting
- 74System prompts vs user prompts
- 75Role prompting and personas
- 76Good prompt vs bad prompt (side by side)
- 77What is RAG (Retrieval Augmented Generation)?
- 78Vector databases and semantic search
- 79Prompting vs RAG vs fine-tuning — which to choose
- 80Multimodal AI (text, image, audio, video together)
- 81Text to image AI
- 82Text to video AI
- 83Text to speech and speech to text
- 84AI music generation
- 85AI coding assistants
- 86Open source models vs closed models
- 87Small models vs large models
module 6 · intermediate AI Agents and Automation AI that does the work, not just the talking.
- 88What is an AI agent?
- 89Chatbot vs assistant vs agent
- 90Tool use and function calling
- 91Memory in AI agents
- 92Planning and reasoning in agents
- 93Multi-agent systems (agents working together)
- 94Model Context Protocol (MCP) — connecting AI to your tools
- 95Workflow automation with AI (n8n, Make, Zapier style)
- 96Building your first AI agent (no code)
- 97When agents fail, and how to control them
module 7 · beginner to intermediate Data, Tools, and Building What you need to actually build something.
- 98Where does AI data come from?
- 99Structured vs unstructured data
- 100Data cleaning (the boring but vital step)
- 101Data labelling and annotation
- 102What is big data?
- 103What is an API?
- 104Python for AI — a gentle start
- 105Key tools: NumPy, Pandas, scikit-learn
- 106TensorFlow vs PyTorch
- 107Google Colab and Jupyter Notebook
- 108No-code AI tools for non-programmers
- 109Cloud AI services (AWS, Google, Azure, Anthropic, OpenAI)
- 110How much does AI cost to use?
- 111GPUs, TPUs, and why AI needs strong computers
module 8 · intermediate Putting AI Into Real Use From a demo on your laptop to a system people trust.
- 112What is model deployment?
- 113Training vs inference
- 114What is MLOps?
- 115Model monitoring and model drift
- 116Edge AI (AI on your phone and devices)
- 117Quantization and making models smaller
- 118Scaling: from 10 users to 10 million
- 119Testing an AI system
- 120Keeping AI systems secure
- 121Prompt injection and AI attacks
module 9 · beginner AI in the Real World How real industries use AI today.
- 122Computer vision — how AI sees
- 123Natural Language Processing — how AI reads
- 124Speech recognition — how AI hears
- 125Robotics and AI
- 126Self-driving cars
- 127AI in healthcare
- 128AI in banking and fraud detection
- 129AI in farming and agriculture
- 130AI in education
- 131AI in retail and e-commerce
- 132AI in travel and tourism
- 133AI in logistics, shipping, and freight
- 134AI in manufacturing and factories
- 135AI in construction and real estate
- 136AI in marketing and advertising
- 137AI in customer support
- 138AI in recycling and waste management
- 139AI in government and public services
- 140AI for small business owners
module 10 · beginner Ethics, Safety, and the Future Everyone should read this module.
- 141AI bias — why AI can be unfair
- 142AI and your privacy
- 143Explainable AI (why did the AI decide that?)
- 144Deepfakes and fake news
- 145Will AI take my job?
- 146AI and copyright
- 147AI laws and regulation around the world
- 148AI safety and alignment
- 149How to use AI responsibly
- 150The energy and water cost of AI
- 151What is AGI? Is it close?
- 152The future of AI — what experts agree and disagree on