TAUGHT BY A CAMBRIDGE PHD SCHOLAR
A hands-on program. No prior experience required.
For students in Grades 8 to 12. No prior quantum physics, machine learning, or coding experience required.
START NOW
Advanced technology is often introduced only at university. It does not have to be. With a laptop, curiosity, and three weekends, a school student can understand how a qubit works and actually apply it.
You will not sit and watch. You will write the code, run real quantum circuits, train a model, and end up with something you built and can explain to anyone.
And the Python and machine learning skills you pick up on the way stay useful far beyond quantum.
LEARNING OUTCOMES
Explain qubits, superposition, and entanglement in plain language, and with working code.
Build and execute quantum circuits in Python using PennyLane and Google Colab.
Describe how machine learning models learn, and train a simple model yourself.
Build, train, and evaluate a quantum machine learning classifier on real data.
Articulate clearly what quantum computers can and cannot do today.
Complete a technical project with teammates and present it to an audience.
AT A GLANCE
3-weekend online program
Starts 14 November
(3 weekends · 9am EDT · 90 minutes)
Students in Grades 8 to 12. No prior experience required
Google Colab, runs in the browser with nothing to install
Python and PennyLane, the quantum machine learning library
Build and train your own quantum classifier, in teams of 2 to 3
USD 499USD 599 standard
Includes all six live sessions, project mentorship, and the Python Starter Pack.
PRIOR EXPERIENCE None required. Basic Python helps, and a free Python Starter Pack is included with enrolment.
YOUR TRAINER
PHD SCHOLAR, DAMTP
UNIVERSITY OF CAMBRIDGE
Rakesh could have spent this term entirely inside a research group. He would rather spend part of it de-mystifying quantum computing. He has taught mathematics and computer science to students of every level for more than five years, and won a Best Teacher Award in 2021 for it, because he is unusually good at making a hard idea feel obvious.
His day job is the subject he is teaching here: a PhD scholar at the University of Cambridge's Department of Applied Mathematics and Theoretical Physics, supported by the Cambridge International Scholarship, working on quantum computing and machine learning. Along the way he has researched with RIKEN in Tokyo, built quantum language models on real quantum hardware with Northeastern University, and applied quantum models to financial data with Singapore Management University.
So students learn from someone doing this work now, taught by someone who has spent years learning how to explain it.
RIKEN, TOKYO
NORTHEASTERN UNIVERSITY
SINGAPORE MANAGEMENT UNIVERSITY
CURRICULUM
Ninety minutes each: short visual explanations combined with guided hands-on coding. Weekend 3 is a team project sprint.
WEEKEND 1
SAT 14 NOV
Why quantum computers exist, plus superposition and measurement. Run your first quantum circuit and flip a real “quantum coin.”
SUN 15 NOV
Quantum gates as rotations. Build multi-qubit circuits, create an entangled pair, and see “spooky” correlations in your own data.
WEEKEND 2
SAT 21 NOV
What machine learning really is: models, training, predictions. Train your first model in about 20 lines of Python.
SUN 22 NOV
Put it together: encode data into qubits, build a variational quantum circuit, train a quantum model. Hype vs. reality, honestly discussed.
WEEKEND 3 · TEAM PROJECT SPRINT
SAT 28 NOV
In teams of 2 to 3, build your own quantum classifier from a guided template, with tiers of challenge to stretch every level.
SUN 29 NOV
Complete the project, then present your results: what you built, how well it worked, and what surprised you.
THE OUTCOME OF WEEKEND 3
Both sessions of Weekend 3 are one team project sprint. Working in teams of 2 to 3, students take a guided quantum-classifier template and make it their own: tuning the model, changing how data is encoded, or trying a new dataset, depending on how far they want to push. Every team presents their results in the closing showcase, so the finished project is the stated outcome of the program.
WHO SHOULD JOIN