Getting Started with Applied Quantum Optimization

D-Wave’s official applied optimization course focuses on the practical side of quantum computing: identifying which business problems are good candidates for quantum-classical hybrid solvers and formulating them correctly before writing a single line of code.

The course covers the “problem discovery” and “problem description” phases of quantum application development — the steps that happen before any coding. This is unusual for a quantum computing course and fills a real gap: most quantum education focuses on algorithms and circuit mechanics, not on how to recognize a problem that quantum optimization can actually help with.

What you’ll learn

• Characteristics that make an optimization problem suitable for D-Wave’s Advantage system and hybrid solvers
• How to evaluate optimization use cases in business and operational contexts
• How to define an optimization problem in plain language before formalizing it mathematically
• How to determine a problem’s objectives, constraints, variables, and parameters
• How to assess and communicate the business value of applying quantum-classical hybrid technology

Course structure

The course is organized into four modules delivered asynchronously. Access is provided for 30 days from registration.

• Module 1: Optimization and Quantum Computing — What makes a problem an optimization problem, and why quantum annealing is well-suited for certain classes of them
• Module 2: Problem Discovery — How to identify optimization opportunities within an organization and evaluate them against quantum feasibility criteria
• Module 3: Problem Description — How to formally describe a problem: variables, objectives, constraints, and parameters
• Module 4: Quantum Business Case — How to articulate the value of quantum-classical hybrid approaches to technical and non-technical stakeholders

Who is this for?

• Business analysts and solution architects evaluating D-Wave for real-world optimization use cases
• Developers who want to understand how to scope a quantum optimization project before writing QUBO code
• Quantum enthusiasts who want to understand how D-Wave’s annealing approach differs from gate-based quantum computing in practice
• Anyone moving from the “what is quantum computing” level to “how do I apply it to a real problem”

Prerequisites

No math, physics, or quantum computing background is required. Basic familiarity with organizational processes and business KPIs is described as helpful but not mandatory.

Context: D-Wave’s approach

D-Wave’s Advantage system is a quantum annealer, not a gate-based quantum computer. It cannot run Shor’s or Grover’s algorithms. What it can do is solve certain combinatorial optimization problems — routing, scheduling, portfolio optimization, constraint satisfaction — at a scale no gate-based system currently matches for real business problems.

This course teaches the layer before the code: how to recognize a problem that fits the annealing model and how to describe it precisely enough to formalize as a QUBO (Quadratic Unconstrained Binary Optimization) problem. That problem formulation step is where most applied quantum projects succeed or fail.

For hands-on QUBO and Ocean SDK programming, see D-Wave’s Leap developer platform and the Ocean SDK tutorials.