SYSEN 5860

Quantum Computing and Artificial Intelligence

Course Description

Course information provided by the 2020-2021 Catalog.

Introduces the current status of quantum computing and its applications for artificial intelligence. Topics include Qubit states, entanglement, quantum circuits, Ising model, basics of quantum algorithms, adiabatic quantum computing and quantum annealing, noisy intermediate scale quantum (NISQ) computing, quantum optimization, quantum machine learning and quantum neural network. Learn how to access and use quantum computing resources, set up optimization and machine/deep learning problems to be solved with quantum computing, and develop quantum algorithms for artificial intelligence applications.

Prerequisites/Corequisites Preferred prerequisite: CHEME 6800/SYSEN 6800 and CHEME 6880/SYSEN 6880.

Outcomes

• Understand the concepts, theory and methods of quantum computing.
• Demonstrate an ability to apply knowledge of quantum computing for solving practical problems in artificial intelligence.
• Identify the engineering application of quantum computing to the optimize engineering systems and analyze large-scale datasets in machine learning.

When Offered Spring, Summer, Winter.

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