The University of Alabama 3 credits PH
This course explores the intersection of Quantum Computing and Machine Learning, two emerging technologies of the future. Through hands-on tutorials with industry-standard tools like Qiskit, PennyLane and Ocean, the course introduces modern quantum machine learning algorithms and methods that can be used to solve real-world problems. Optimization problems will be solved through the application of quantum annealing, Quantum Approximate Optimization Algorithm, Grover adaptive search, and Variational Quantum Eigensolvers. Quantum machine learning models like quantum support vector machines, quantum neural networks, quantum generative adversarial networks and others will be built, trained and benchmarked against their classical counterparts.
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