ELEN E4730
Quantum Optimization and Machine Learning
An introduction to the recent development in quantum optimization and quantum machine learning using gate-based Noisy Intermediate Scale Quantum (NISQ) computers. IBM’s quantum programming framework Qiskit is utilized. Qbits, quantum gates and quantum measurements, quantum algorithms (Grover’s search, Simon’s algorithm, quantum Fourier transform, quantum phase estimation) quantum optimization (quantum annealing, QAOA, variational quantum eigensolver), quantum machine learning (quantum support vector machine, quantum neural networks)
Prerequisites & course information
Prerequisites: probability theory, linear algebra
Sources
- Course catalogue ↗2026-2027