Courses to Learn Quantum Computing
A curated path from zero to advanced: hands-on SDK courses, university lectures, interactive codebooks, and the math you need — most of them free.
1 Beginner
Start here — no prior quantum knowledge required.
IBM Quantum Learning
IBM
IBM's official learning hub: interactive lessons and courses that teach quantum information and Qiskit, with free access to IBM Quantum simulators and real hardware.
Basics of Quantum Information
IBM Qiskit
A rigorous, beginner-friendly course on the mathematics of qubits, superposition, entanglement, and measurement — the conceptual foundation for everything else.
PennyLane Codebook
Xanadu
A free, hands-on codebook that teaches quantum computing and quantum machine learning by writing real PennyLane code in your browser, chapter by chapter.
Quantum Katas
Microsoft
Self-paced programming exercises (katas) that teach quantum computing and Q#/Qiskit through hundreds of small, testable tasks.
Quantum Computing for the Very Curious
Nielsen & Matuschak
An essay-style, mnemonic-medium textbook that builds deep intuition for quantum computing using embedded spaced-repetition flashcards.
Introduction to Quantum Computing
Qubit by Qubit (The Coding School)
A structured, cohort-based program (often free for students) that teaches quantum computing from the ground up over a full course.
Essence of Linear Algebra
3Blue1Brown
A visual, intuition-first video series on the linear algebra that underpins quantum computing — the ideal math primer.
2 Intermediate
Build real circuits and hybrid algorithms.
PennyLane Coding Challenges
Xanadu
Bite-sized coding challenges that turn quantum concepts into practice, from basic circuits to variational algorithms and QML.
The Introduction to Quantum Computing
Saint Petersburg State University (Coursera)
A university course covering the core algorithms and principles of quantum computing, auditable for free on Coursera.
Cirq Tutorials
Google Quantum AI
Official Google Quantum AI tutorials for building and simulating circuits with Cirq, including NISQ-era algorithms.
CUDA-Q Academic
NVIDIA
NVIDIA's open teaching materials for GPU-accelerated quantum simulation and hybrid quantum-classical programming with CUDA-Q.
3 Advanced
Theory, proofs, and research-level material.
8.370x — Quantum Information Science I
MITx on edX
MIT's graduate-level introduction to the theory of quantum information — qubits, protocols, and algorithms — auditable for free on edX.
Quantum Computation and Quantum Information
Nielsen & Chuang
The definitive graduate textbook on quantum computation and information — the standard reference for serious study.
Quantum Algorithm Zoo
Stephen Jordan
A comprehensive, continually updated catalogue of quantum algorithms with references — a reference for advanced learners and researchers.
Frequently Asked Questions
How to choose and get the most out of these quantum computing courses.
What is the best free course to start learning quantum computing?
For an absolute beginner, IBM Quantum Learning and the PennyLane Codebook are the two strongest free starting points: both are hands-on, browser-based, and require no prior quantum knowledge. If you prefer reading, 'Quantum Computing for the Very Curious' explains the core ideas with built-in spaced repetition.
Do I need to know math before learning quantum computing?
A working grasp of linear algebra (vectors, matrices, complex numbers) makes quantum computing far easier. You do not need it to start the beginner courses, but reviewing 3Blue1Brown's 'Essence of Linear Algebra' in parallel is highly recommended before moving to intermediate material.
Can I learn quantum computing for free?
Yes. Most courses on this page are completely free, and university courses on edX and Coursera can be audited at no cost. Combined with free simulators and free real-hardware access, you can go from beginner to running algorithms on a real QPU without paying anything.
Which course should I take to write quantum code?
Choose a course tied to an SDK you can install for free: the PennyLane Codebook and Coding Challenges for quantum machine learning, the Microsoft Quantum Katas for algorithm practice, or Cirq and CUDA-Q tutorials for simulation. HLQuantum lets you reuse the same code across all of these backends afterwards.