Foundations for Quantum Programming

This online course is an optional prerequisite for the Quantum Programming Core training. It supports the math and Python skills needed to successfully complete Quantum Programming Core and use D-Wave annealing quantum computers to solve optimization problems. Learners who successfully complete this course will better understand how to determine optimization problem objectives, define problem variables, and represent problems mathematically, graphically, and programmatically.

Course materials include recorded presentations, quizzes, and programming activities. The course requires about 10 hours total to complete. Learners have access to the course for 180 days (about six months) from the date of enrollment.

All purchases are in USD.

Learning Objectives Prerequisites

Identify optimization problem objectives and variables.
Represent problem objectives as math expressions.
Represent problem constraints as equalities and inequalities.
Convert problem constraints to penalty expressions.
Combine optimization problem objectives and constraints into an appropriate QUBO function.
Represent algebraic functions graphically and using matrices.
Write basic Python programs to represent, setup, and organize optimization problems.

None!

For those taking this course as the optional prerequisite for Quantum Programming Core, we recommend completing this course before starting Quantum Programming Core, but before the end of your 180 days of access.

Not sure if you need to take this prerequisites course? You can take this self-assessment to help you determine where to start your quantum training journey.

Course Outline

Module 1: Course Overview

Module 2: Problem Variables

Module 3: Math Used in Problem Formulation

Module 4: Math Used in Formulating Problem Constraints

Module 5: Ways to Represent Optimization Problems

Module 6: Representing Optimization Problems in Code

Price: $350.00
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