5 courses · 13 tutorials
D-Wave
Learn to identify and describe optimization problems suited for D-Wave's quantum-classical hybrid technology. Covers problem discovery, constraint definition, and building a quantum business case. No math or physics background required.
D-Wave
Preparatory course building the math and Python skills needed before D-Wave's Quantum Programming Core. Covers QUBO formulation, quadratic models, constraint writing, and Python for optimization. Optional but recommended for developers without strong math backgrounds.
D-Wave
D-Wave's free introductory course demystifying quantum computing for general audiences. Covers how quantum computers work, annealing vs gate-model systems, and real-world optimization use cases. No background required.
D-Wave
D-Wave's flagship developer training: 35 hours of hands-on instruction covering QUBO formulation, Ising models, Ocean SDK, hybrid solvers, and real-world portfolio optimization. Includes virtual office hours with D-Wave experts. Multiple 2026 sessions available.
D-Wave
D-Wave's bundle combining Quantum Programming Core with one additional month of unlimited Leap Quantum Cloud access. 35 hours of developer training plus hands-on QPU access for first-time Leap users. Approximately 6 weeks total.
Learn how to formulate the Traveling Salesman Problem and graph coloring as QUBOs and BQMs using D-Wave Ocean SDK, then solve them with LeapHybridSampler and interpret the results.
Use D-Wave's Constrained Quadratic Model (CQM) sampler to solve optimization problems with explicit constraints, eliminating the need for manual QUBO penalty encoding.
Formulate the graph coloring problem as a QUBO and solve it on D-Wave using the Ocean SDK.
Write your first quantum annealing program with D-Wave Ocean, formulate a simple QUBO problem and solve it with the simulated annealing sampler.
Install the D-Wave Ocean SDK, formulate a simple optimization problem as a QUBO, and solve it using D-Wave's quantum annealer or simulator.
Learn how logical problem variables map to physical qubits through minor-embedding, and how to diagnose and fix chain breaks on D-Wave hardware.
Use D-Wave's Leap hybrid solver service to solve large optimization problems that are too big for the QPU alone: LeapHybridSampler, problem formulation, and interpreting solutions.
Learn the full D-Wave hybrid workflow: define optimization problems as BQMs and CQMs, use LeapHybridSampler for large-scale solving, apply SteepestDescentSolver for local refinement, and decide when hybrid outperforms pure classical or QPU-only approaches.
Solve large optimization problems with D-Wave Leap hybrid solvers that combine classical heuristics and quantum annealing.
Learn how to formulate combinatorial optimization problems as QUBO matrices for D-Wave, including penalty terms for constraints and a worked number partitioning example.
A clear comparison of quantum annealing and gate-based quantum computing: how they work, what problems they solve best, and when to choose each approach.
Use D-Wave Ocean's SimulatedAnnealingSampler to test QUBO formulations locally before committing to quantum hardware.
Learn D-Wave's Ocean SDK for quantum annealing, formulate combinatorial optimisation problems as QUBO models and solve them on the world's largest quantum annealing processors.