SYSEN 5860 - Quantum Computing and Artificial Intelligence

Spring, Summer, Winter. 3 credits. Student option grading.

Preferred prerequisite: CHEME 6800/SYSEN 6800 and CHEME 6880/SYSEN 6880. Co-meets with CHEME 6860.

F. You.

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.

Outcome 1: Understand the concepts, theory and methods of quantum computing.

Outcome 2: Demonstrate an ability to apply knowledge of quantum computing for solving practical problems in artificial intelligence.

Outcome 3: Identify the engineering application of quantum computing to the optimize engineering systems and analyze large-scale datasets in machine learning.