Intuitive Learning of Quantum Computing
This course provides the end-to-end description from quantum phenomena to quantum computing hardware, software, and algorithms to hands-on use of IBM Q systems. This course is specifically designed to educate business users of quantum computers without requirements of advanced physics and mathematics for quantum mechanics. The course will compose the following four parts:
I: Why we need to engage in quantum computing education? How can we effectively engage quantum computing?
II: Intuitive & graphic explanation of quantum phenomena, including wave-particle duality, superposition, measurement, and entanglement.
III Intuitive & graphic explanation of quantum computing. (IBM Qiskit interactive hands-on practices)
IV: Quantum computing business applications, and examples of quantum computing results.
Course Learning Outcomes:
By the end of this course, students will be able to:
- Recognize basic quantum phenomena that enable the functions of QC algorithms.
- Formulate and implement QC gates using IBM Qiskit software.
- Relate business insights for what QC capabilities could support decision-makers timely and actionable that your organization never had before.
- Gain insights to determine what and how to build QC workforce with right QC tools for the purpose and unique requirements of your organization.
Course Typically Offered: Online (asynchronous) during our Spring and Fall academic quarters.
Software: This course will utilize IBM Qiskit, an open source SDK for working with quantum computers at the level of pulses, circuits and application modules.
Prerequisites: Some basic familiarity with Linear Algebra. A bachelor’s degree or work experience in managing or using computers.
Next step: After completing this course, consider enrolling in the course LEAN Thinking for Big Data Analytics, or courses in our Selected Topics in Artificial Intelligence certificate, or other Technology-related coursework.
Contact: For more information about this course, please contact email@example.com.
Course Number: CSE-41343
Credit: 3.00 unit(s)
Related Certificate Programs: Machine Learning Methods, Selected Topics in Artificial Intelligence
There are no sections of this course currently scheduled. Please contact the Science & Technology department at 858-534-3229 or firstname.lastname@example.org for information about when this course will be offered again.