Intuitive Learning of Quantum Computing

Understand Quantum Computing Through Intuitive Concepts and Real-world Applications This course provides an end-to-end introduction to quantum computing, from fundamental quantum phenomena to practical use of quantum hardware, software, and algorithms through hands-on experience with IBM Q systems.

The course explains quantum concepts using intuitive and graphical methods without requiring advanced physics or mathematics.

You will explore key ideas such as wave-particle duality, superposition, measurement, and entanglement, and then apply these concepts by implementing quantum gates and algorithms using IBM Qiskit on real quantum computing systems.

The course also focuses on business applications of quantum computing and demonstrates how organizations can leverage IBM Q platforms for experimentation, innovation, and data-driven decision-making.

Course Highlights Intuitive and visual explanation of quantum phenomena Core concepts: wave-particle duality, superposition, measurement, and entanglement Hands-on labs using IBM Q systems and Qiskit interactive tools Implementation of quantum gates and basic quantum algorithms Overview of quantum computing hardware and software ecosystems Real-world business applications of quantum computing Workforce readiness and quantum strategy for organizations Course Benefits Learn quantum computing concepts without advanced physics or mathematics Gain practical experience using real quantum computers via IBM Q systems Understand how quantum computing can support business and strategic decisions Identify use cases for quantum technology in your organization Build foundational skills for emerging quantum computing careers Credit earned may be applied toward an academic degree or professional credential, subject to the approval of the receiving institution(s) Course Details and Next Steps Course Typically Offered: Online in Spring and Fall 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.

Next step: After completing this course, consider enrolling in the course LEAN Thinking for Big Data Analytics , or courses in our Machine Learning Methods or Technical Aspects of Artificial Intelligence certificate program Contact: For more information about this course, please contact unex-techdata@ucsd.edu