The full curriculum
Eight courses, 89 chapters — the complete path from the math itself to algorithms, error correction, and honest applications — written so anyone can follow — every concept defined the moment it appears, at least two worked numeric examples per chapter, and every circuit runnable right on the page. The first 3 chapters of each course are free; a free account unlocks the rest until paid plans launch. The 12 foundation lessons are and stay entirely free.
The Math You Actually Need
Course 0: every piece of math the curriculum uses, from powers and probability to complex numbers, radians, and exponential decay — taught from zero, with a real quantum circuit to run in every chapter. Entirely free.
- Read 2^n, √, π, and scientific notation without slowing down
- Multiply probabilities, square amplitudes, and predict counts
- Picture complex numbers as arrows so phases and rotations make sense
Quantum Computing for Developers
From zero to a correct working mental model: qubits, amplitudes, measurement, gates, entanglement — every claim runnable, no physics degree required.
- Explain qubits with amplitudes, not metaphors
- Build and run small circuits and predict their statistics
- Construct and defend a Bell-state experiment
Quantum Circuits: Build, Simulate & Debug
Read, construct, simulate, and debug real circuits: multi-qubit gates, circuit identities, depth, and the debugging habits that catch wrong circuits early.
- Compose multi-qubit circuits fluently
- Debug a circuit by predicting and checking distributions
- Reason about depth and two-qubit cost
Inside Quantum Processors
What the hardware actually is: architectures, topology, native gates, coherence, calibration — and how to read a vendor spec sheet critically.
- Compare superconducting, trapped-ion, and neutral-atom machines honestly
- Read fidelity/coherence figures with their methods and caveats
- Judge which architecture suits a given circuit
Quantum Compilation & Transpilation
How logical circuits become hardware programs: basis translation, layout, routing, optimization — the layer almost nobody teaches, live on our reference compiler.
- Explain why compiled circuits grow, gate by gate
- Trace layout and SWAP-routing decisions on real topologies
- Estimate hardware cost before running anything
Quantum Algorithms from First Principles
Design algorithms, not just run them: oracles and query complexity, Deutsch–Jozsa, Grover, the QFT, phase estimation, Shor (honestly), and variational methods — every one built and measured on the page.
- Derive why interference — not parallelism — powers every quantum speedup
- Build Deutsch–Jozsa, Bernstein–Vazirani, Grover, QFT, and phase-estimation circuits
- State exactly what Shor and variational algorithms can and cannot do today
Errors, Noise & Quantum Error Correction
Why qubits fail and what the industry is doing about it: error models, repetition codes you can run, stabilizers, the surface code, logical-qubit overhead, and mitigation vs correction — the layer every vendor roadmap now lives on.
- Model gate, decay, and readout errors and trace how they propagate
- Encode, corrupt, and correct a logical qubit with runnable repetition codes
- Read vendor logical-qubit roadmap claims with defensible skepticism
Quantum Applications Without the Hype
Where quantum computing actually helps: a use-case evaluation framework, chemistry, optimization, machine learning, cryptanalysis and post-quantum migration, QKD, and networking — each claim classified by evidence, never by press release.
- Evaluate any quantum use-case claim end to end, data loading included
- Formulate a problem as qubits, costs, and a measurable circuit
- Separate post-quantum cryptography from quantum hardware — and know which you need