Labs with results on the page
Eleven notebooks, from coin flips to the quantum switch, show every result in the browser. Each one opens in Google Colab with one click.
Open course · free
Quantum Causal AI
Learn how causes work, then learn how quantum physics changes the question. The course starts with counting objects and fair tests and climbs, one checked step at a time, to current research on quantum causal models, indefinite causal order, and quantum machine learning.
- 80lessons
- 8levels
- 11interactive labs
- 59checked references
- 49videos
- 25podcast episodes
Eight levels, one path
Each level is a teaching guide, not a certificate. Every lesson has a worked example, an exercise with a solution, a self-check, and a lab. A one-minute placement check suggests where to start.
Level 0 · Grades 1-3 · 10 lessonsNotice, count, and askStart with objects, light, choices, and fair tests.
Level 1 · Grades 4-6 · 10 lessonsChance, waves, and fair testsUse fractions and repeated tests to describe uncertain results.
Level 2 · Grades 7-9 · 10 lessonsAlgebra, evidence, and causal mapsTurn verbal questions into variables and models.
Level 3 · High-school bridge · 10 lessonsMathematical tools for modelsBuild the mathematical tools that causal and quantum models use.
Level 4 · Undergraduate · 10 lessonsClassical causal AIUse causal models to define the effect of an action.
Level 5 · Advanced undergraduate · 10 lessonsQuantum informationBuild the state, channel, and measurement tools needed for quantum causal models.
Level 6 · Graduate · 10 lessonsQuantum causal modelsConnect operational quantum theory with causal questions, explicit assumptions, and testable model classes.
Level 7 · Doctoral and postdoctoral · 10 lessonsQuantum Causal AI researchDefine research tasks, audit learning claims, count resources, and build reproducible causal experiments.
See how every lesson connects
The learning map shows all 80 lessons. Pick one to trace everything it builds on and everything it unlocks, then expand the map to full screen to zoom and pan.
What is inside
Checked sources
Every reference was matched against arXiv, Crossref, or the publisher's page. For causal AI the course follows Elias Bareinboim's Causal Artificial Intelligence.
A map and a placement check
An interactive map of all prerequisites, and a short adaptive quiz that suggests a starting level.
Watch and listen
Lectures, explainers, and podcast episodes for every level, including Decoding Causality.
Start where you are
No background is needed for Level 0, and every page stays open, so you can jump ahead or back at any time.