IBM Quantum
Basics of Quantum Information (IBM Learning)
IBM's free interactive introduction to quantum information. Covers single and multi-qubit states, quantum circuits, and entanglement with interactive exercises.
IBM runs the largest publicly accessible fleet of real quantum computers. The courses below are the free IBM Learning and Qiskit material.
IBM's quantum computing program has three properties that set it apart from other learning options.
IBM operates a fleet of utility-scale quantum processors accessible over the cloud, including 156-qubit Heron systems. No other provider gives learners free access to hardware at this scale. Running code on real quantum hardware, with real noise, real gate errors, and real decoherence, is invaluable experience that simulators cannot fully replicate.
Qiskit has the largest open-source community of any quantum computing SDK, with hundreds of contributors, extensive documentation, and an active forum. Learning Qiskit gives you access to the widest range of tutorials, textbook examples, and community help. It also has the strongest job market signal: most quantum computing job listings that specify a framework mention Qiskit.
IBM Learning provides structured courses from introductory to advanced without a paywall. You do not need an IBM Cloud account to access most content. Courses are regularly updated as Qiskit and IBM's hardware roadmap evolve, so the material stays current with the state of the field.
Courses from IBM Learning and the Qiskit ecosystem, beginner first.
IBM Quantum
IBM's free interactive introduction to quantum information. Covers single and multi-qubit states, quantum circuits, and entanglement with interactive exercises.
IBM Quantum
IBM's free four-hour guide for teams starting a quantum initiative. Covers assembling a team, early-stage goals, partners, and metrics. Aimed at project leaders, not circuit programmers.
IBM Quantum
Dr. Elisa Bäumer and Carmen Recio Valcarce, IBM Quantum
Two-week free Qiskit course on openHPI, taught by IBM Quantum researchers. Deutsch-Jozsa and Grover, written out in code.
Qiskit
IBM Quantum / Qiskit Team
The original Qiskit Textbook, now archived on GitHub. Gates and circuits, Grover, Shor, error correction, and quantum machine learning, as Jupyter notebooks.
IBM Quantum
IBM's free three-hour course for a business audience: what the machines do, and where a company might use one. Optional Credly badge after IBM's exam.
IBM Quantum
IBM SkillsBuild
IBM SkillsBuild's free beginner learning content on quantum computing fundamentals. Visual learning activities and virtual labs covering qubits, superposition, entanglement, quantum gates, and basic circuit building.
IBM Quantum
Olivia Lanes (IBM Quantum)
IBM Quantum Learning, taught by Olivia Lanes. The notebooks use a quantum computer from the start. Optional Credly badge after IBM's exam.
IBM Quantum
Free intermediate course from IBM covering Grover's search, quantum phase estimation, and the fundamentals of quantum algorithm design.
IBM Quantum
IBM's free six-hour course on hybrid quantum-classical workflows. Written for people who know either quantum computing or HPC, not both. Covers programming models, SQD and SKQD, and scheduling QPUs next to CPUs and GPUs.
IBM Quantum
IBM Quantum (Victoria Lipinska and others)
IBM's free introductory VQE course aimed at chemistry. Hamiltonians, ansatze, classical optimizers, ground-state energies and bond lengths with Qiskit patterns. About 6 to 10 hours.
IBM Quantum
Max Rossmannek, Julian Schuhmacher, Alexander Miessen, and Laurin Fischer, IBM Quantum
Free openHPI course on quantum simulation for chemistry and materials science, developed with IBM Quantum. Covers the second quantization, molecular Hamiltonians, VQE for molecular ground states, and Qiskit Nature.
IBM Quantum
IBM's free course on utility-scale quantum computing. Covers running large circuits on real IBM hardware, error mitigation, and near-term application areas using Qiskit Runtime.
IBM Quantum
John Watrous
John Watrous's four-course video lecture series covering quantum information theory, algorithms, error correction, and the general formulation of quantum operations. Graduate-level rigor, freely available.
IBM Quantum
IBM's free eight-hour course on hybrid variational algorithms. Covers cost functions, ansatze, optimizers, VQE, SSVQE and VQD, using IBM Quantum primitives.
IBM Quantum
John Watrous
John Watrous's fourth IBM Learning course. Quantum error-correcting codes, the stabilizer formalism, CSS codes, the toric and surface codes, and fault-tolerant computation. About 15 hours. Free, with an optional Credly badge.
IBM Quantum
IBM's free ten-hour course on quantum approaches to matrix diagonalization, including VQE, sample-based quantum diagonalization (SQD) and sample-based Krylov methods, with discussion of classical versus quantum scaling.
IBM Quantum
IBM's free ten-hour Quantum Learning course on quantum methods in machine learning, including variational quantum classifiers and quantum neural networks implemented in Qiskit.
IBM Quantum
Dr. Christa Zoufal, Julien Gacon, Dr. David Sutter (IBM Quantum)
Free openHPI course, with IBM Quantum Research, on quantum machine learning: variational classifiers, quantum kernels, and QGANs, in Qiskit.
IBM Quantum
Julien Gacon, Dr. Daniel J. Egger, Dr. Stefan Woerner, Lucia Cuervo Valor (IBM Quantum)
Free openHPI course on quantum approaches to combinatorial optimization, developed with IBM Quantum. Covers QAOA, VQE, and the quadratic unconstrained binary optimization (QUBO) framework with Qiskit implementation.
Creating a free IBM Quantum Platform account at quantum.cloud.ibm.com gives you access to IBM's open quantum systems through the Open Plan, which includes a monthly allowance of QPU time. The free tier includes:
Run circuits on IBM's publicly available quantum processors over the cloud. Free accounts access IBM's open systems, which are the same physical hardware used for research, not stripped-down simulators.
IBM's cloud execution environment, Qiskit Runtime, manages job submission, result retrieval, and primitive-based execution. Primitives like Sampler and Estimator abstract the hardware details, making it easier to write portable quantum code.
Free-tier jobs are placed in a shared queue. Wait times are typically minutes to a few hours depending on system demand. IBM's job scheduler optimizes placement across available systems. For time-sensitive work, paid plans offer priority queue access.
Qiskit's open-source Aer simulator runs locally and can mimic quantum hardware noise models. It is useful for testing and debugging circuits before submitting to real hardware, where each job consumes your free QPU time allowance.
Choosing a quantum computing platform is a practical decision based on your goals. Here is an honest comparison.
| Platform | Framework | Best for | Hardware access |
|---|---|---|---|
| IBM / Qiskit | Qiskit | Beginners, general algorithms, broad community | Free (shared queue) |
| Google / Cirq | Cirq | Research, superconducting qubit experiments | Limited public access |
| Xanadu / PennyLane | PennyLane | Quantum machine learning, hybrid algorithms | Simulator + cloud backends |
| IonQ | Cirq / Qiskit compatible | Trapped-ion hardware, high gate fidelity | Paid (Amazon Braket, Azure) |
For most learners, IBM and Qiskit is the right starting point. The free hardware access, extensive documentation, and large community make the learning curve manageable. You can always branch out to PennyLane for machine learning applications or Cirq for Google-ecosystem research later.