Implementation of Applied Quantum Optimization Models

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This is the third course in the Applied Quantum Optimization learning path. It equips learners with the knowledge and skills to complete the software implementation and testing steps in developing quantum applications.

Learners will be able to code mathematical formulations of optimization problems for D-Wave’s nonlinear solver, known as the Stride™ hybrid solver. Learners will also be able to validate optimization models, interpret solver outputs into business terms, and use key performance metrics to evaluate comparable models.

This intermediate-level course is appropriate for individuals involved in implementing optimization models in code.

All course content is asynchronous online, and up to 10 minutes of access to the Leap™ quantum cloud service is provided for the duration of the course. Additional support is available from D-Wave instructors through discussion boards, email, and optional online office hours.

This course requires approximately 20-25 hours to complete.

After registration, learners can enter the online course and indicate when they are ready to begin their 30-day access to the Leap quantum cloud service and all course content. For courses purchased through the website, learners must indicate their start date within 180 days of registration. For courses purchased through a quote issued by D-Wave, learners must redeem the voucher issued by D-Wave within the applicable subscription period stated in such quote and indicate their start date within 180 days of such redemption. Once a learner indicates their start date, they will have 30 days of access to the online course, including the Leap quantum cloud service and all course content.

  • Code mathematical formulations of optimization problems for D-Wave’s Stride hybrid solver.
  • Use the Ocean™ SDK to build and submit problems.
  • Validate optimization models.
  • Interpret Stride hybrid solver outputs into business terms.
  • Use key performance metrics to evaluate equivalent optimization problem models.

Although there are no formal requirements before enrolling in this course, we recommend the following prerequisites:

  • Completion of the Getting Started with Applied Quantum Optimization course, which prepares you to write a clear and comprehensive optimization problem description, including objective(s), constraint(s), decision variables, and parameters.
  • Completion of the Problem Formulation for Applied Quantum Optimization course, which supports you in converting your plain-language optimization problem description into mathematical models.
  • Intermediate Python programming experience.
  • Access to the online course for 30 days from your date of start indication.
  • Instructor support via asynchronous discussion boards and live Zoom office hours.
  • Up to 10 minutes of access to the Leap™ quantum cloud service to complete hands-on coding activities.

Course Outline

Module 1 (Optional): Python Review

Module 2: Code Mathematical Models

Module 3: Examples of Model Implementation

Module 4: Evaluate Optimization Models

Price: $500.00
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