Teaching

Quantum Integer Programming and Machine Learning (47-779 / 47-785, 18-819F)

At Carnegie Mellon University Prof. Bernal designed and co-taught this course that focuses on introducing concept in discrete optimization, machine learning, and quantum computing for practitioners. From a perspective that does not require any background in quantum physics, and with a strong focus on practical problems, we introduce concepts of integer programming, artificial intelligence, and quantum methods to address these problems. The course wraps up with a practical project where students implement solutin algorithms in actual quantum computers and benchmark them against state-of-the-art classical methods. Course website can be found here.