IBM Quantum Learning’s walkthrough of near-term variational algorithms. The course page describes a modular workflow: a cost function, an ansatz that explores a parameterised search space, and a classical optimizer. Lessons include reference states, N-local circuits, barren plateaus, and extensions such as subspace-search VQE and variational quantum deflation.
Code examples use Qiskit primitives (Sampler and Estimator). IBM positions the course as a starting place for researchers and developers who want utility on non-fault-tolerant machines, and points back to Basics of Quantum Information for the theory.
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For chemistry-specific VQE, use Quantum Chemistry with VQE. For running large circuits, Quantum Computing in Practice.
Who it is for
Developers who can already write a Qiskit circuit and want the variational loop, not a first course in qubits.
Topics covered
Start this course
Variational Algorithm Design (IBM Learning) is free on IBM Quantum, at intermediate level, and runs 8 hours. A certificate is included.
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