Learn AI properly.
Python, all the maths, machine learning, deep learning, NLP, computer vision, generative AI, robotics, safety and AGI. Every topic has a clear definition, a full explanation, its formulas, code that runs in your browser and a quiz.
- 1. Log inYour progress is saved on every device.
- 2. Answer a few questionsYour goal, and what you already know. About a minute.
- 3. See a suggested pathWhich modules, in what order, and what you can skip.
- 4. Read whatever you wantFollow the path, or don't. Nothing is ever locked.
- 3
- levels
- 37
- modules
- 593
- topics in the syllabus
- 14
- suggested learning paths
166 topic pages are complete today. The rest are being written in order, and each module shows what's ready.
the whole syllabus
One map, from start to finish.
Three levels, Beginner, Intermediate and Advanced, from the first definition of AI to open research. Start at the top, or jump to whatever you need.
level 1
Beginner: Understanding Artificial Intelligence
- B1 Introduction to Artificial Intelligence · 20
- B2 How Artificial Intelligence Works: Data and Learning · 23
- B3 Applications of Artificial Intelligence · 18
- B4 Domains of AI: Vision, Language, Speech and Robotics · 22
- B5 Generative AI and Conversational Assistants · 15
- B6 Responsible and Safe Use of AI · 21
- B7 Data Literacy and Visualisation · 18
- B8 Computational Thinking and the AI Project Cycle · 20
- B9 AI, Society and the Future · 8
- B10 Beginner Capstone: AI for Social Good · 8
level 2
Intermediate: Building with Artificial Intelligence
- I1 Python Programming for AI · 34
- I2 Working with Data: NumPy, pandas, SQL and Visualisation · 21
- I3 Mathematics for AI · 16
- I4 Problem Solving and Reasoning: Classical AI · 16
- I5 Machine Learning Foundations · 21
- I6 Neural Networks and Deep Learning Essentials · 16
- I7 Computer Vision in Practice · 12
- I8 Natural Language Processing in Practice · 13
- I9 Generative AI and Large Language Models in Practice · 16
- I10 Responsible AI in Practice · 13
- I11 Intermediate Capstone: An End-to-End AI Project · 10
level 3
Advanced: Engineering and Researching Artificial Intelligence
- A1 Supervised Machine Learning in Depth · 27
- A2 Unsupervised Learning and Applied Machine Learning · 15
- A3 Advanced Mathematics for AI · 15
- A4 Probabilistic Reasoning, Decisions and Game Theory · 12
- A5 Deep Learning with PyTorch · 16
- A6 Computer Vision with Deep Learning · 14
- A7 Sequence Models, Transformers and Modern NLP · 14
- A8 Large Language Models: Training, Adaptation and Evaluation · 15
- A9 Retrieval-Augmented Generation and Knowledge Systems · 11
- A10 AI Agents and Autonomous Systems · 11
- A11 Generative Models and Multimodal AI · 12
- A12 Reinforcement Learning · 12
- A13 MLOps, Deployment and AI Infrastructure · 17
- A14 AI Security, Safety and Governance · 13
- A15 Frontier AI: AGI and Open Research Problems · 16
- A16 Research Methods and Advanced Capstone · 12
how every topic is written
The same format, on every page.
So you always know where the definition is, where the formula is and where to test yourself.
01
Definition
The correct definition, right at the top.
02
In simple words
The same idea with an everyday example.
03
Why it matters
Where it's used, and what breaks without it.
04
How it works
The full written explanation, step by step.
05
The maths
Each formula, each symbol explained, then real numbers.
06
Code
Python you can run and edit in the browser.
07
Try it yourself
An interactive activity, where we have one.
08
Common mistakes
What people get wrong, and how to avoid it.
09
Check yourself
A quiz where every answer explains why.
10
Summary
The key points, then the next topic.
the people behind it
Meet the minds who started AI.
Tap anyone to open their profile and ask Bitu about them. Real, openly licensed photographs. Photo credits
Ready to start?
Create an account, answer a few questions, and see where we'd suggest you begin.