Quantum Artificial Intelligence

4.0 credits

This course will focus on practical quantum computational approaches to machine learning, clustering, classification, and optimization algorithms. Topics include quantum K-means, quantum support vector machines, quantum principle component analysis, the Quantum Approximate Optimization Algorithm (QAOA), the Variational Quantum Eigensolver (VQE), and quantum neural networks. Both quantum circuit and adiabatic computing models will be examined as well as the design of Hamiltonians for specific problems. Most programming assignments will use the Qiskit (Python based) environment.