Applied Quantum Computing I: Fundamentals (Purdue)

This is the foundational course in Purdue University’s three-part Applied Quantum Computing series on edX, taught by Professor Pramey Upadhyaya. It teaches the fundamental postulates of quantum mechanics and, importantly, how those postulates map onto the present-day models of quantum information processing: computation, simulation, optimization, and machine learning. It is free to audit, with a verified certificate available for a fee.

The course is engineering-oriented rather than purely physics-theoretical. It establishes the mathematical and conceptual groundwork - qubits, superposition, measurement, and the structure of quantum operations - that the later courses build on. Completing Fundamentals is an explicit prerequisite for the Hardware and the Algorithm and Software courses in the series, so it functions as the gateway to the full Purdue program.

Who is this for?

Engineering and physical-science students and professionals who want a rigorous, applications-aware foundation in quantum computing from a major research university. It is well suited to those planning to continue into the full Applied Quantum Computing series or the Purdue Quantum Technology MicroMasters.

Prerequisites

A solid undergraduate background in linear algebra is the most important requirement. Familiarity with differential equations and basic physics will help, but the course develops the quantum mechanics it needs from the postulates rather than assuming a prior quantum course.