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IBM Quantum Computer Programming
Quantum Algorithms / Quantum Approximate Optimization Algorithm
from qiskit_ibm_runtime import QiskitRuntimeServicefrom qiskit.transpiler.preset_passmanagers import generate_preset_pass_manager# Prepare the QAOA circuit for IBM quantum hardwareservice = QiskitRuntimeService()pass_manager = generate_preset_pass_manager(backend=backend, optimization_level=3)isa_circuit = pass_manager.run(qaoa_circuit)IBM Quantum Computer Programming with Hands-On Coding
A structured asynchronous course that moves from quantum foundations to practical algorithm implementation using Python, Qiskit and IBM quantum systems.
About this course
This course offers a comprehensive introduction to quantum computing, beginning with the fundamentals and progressing to advanced algorithm design and implementation. No prior knowledge of quantum computing or quantum physics is required, although familiarity with matrix-vector multiplication is expected.
You will study the mathematics of quantum computing, create quantum gates and circuits, and implement the Quantum Approximate Optimization Algorithm (QAOA) on IBM quantum computers. With a strong focus on practical applications, the course is suitable for both beginners and experienced programmers.
Trusted by Researchers and Professionals from Leading Global Universities and Companies
Develop a rigorous foundation in quantum mechanics and the mathematical formalism required for quantum computing.
Work with leading quantum SDKs at an advanced level and apply them effectively in research and development.
Develop end-to-end workflows with Qiskit and IBM Quantum, from circuit design and transpilation to primitives, Runtime services, backend selection, job execution and result analysis on simulators and quantum hardware.
Become familiar with current implementation techniques across the Braket SDK, simulators, quantum tasks, hybrid jobs and managed quantum-hardware access.
A preconfigured browser-based environment with leading quantum SDKs ready for coding, simulation and execution.
Optimization, finance, logistics, healthcare and quantum machine learning.
From quantum foundations to SDKs, QuantumLab and applications.
Develop a rigorous understanding of the mathematical foundations of quantum computing, quantum circuits, algorithm implementation, and the methods used to execute programs on simulators and quantum hardware.
The curriculum covers advanced use of Qiskit and IBM Quantum, as well as Amazon Braket. Through QuantumClass, you also gain access to QuantumLab—a preconfigured browser-based quantum IDE with leading SDKs ready for coding, simulation, transpilation, job submission, and supported quantum-hardware execution. Applied study extends to optimization, finance, logistics, healthcare, and quantum machine learning.
Quantum Fundamentals for Future Innovation
“In general, it’s not just about understanding quantum computing but, more importantly, understanding the fundamentals so I can then apply them to my role and think about how products and services might be developed in the future.”
Shared this insight during the QuantGates workshop at the Barbican, London.
Begin your next stage of quantum learning.
Access structured lessons, practical assignments and a learning community built around serious quantum computing education.