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Courses - Fall 2023
MSQC
Quantum Computing
MSQC601
Mathematics and Methods of Quantum Computing
Credits: 3
Grad Meth: Reg
This course will provide the student with the necessary physical intuition and background information on quantum physics to be able to understand and appreciate a variety of applications in quantum computing such as quantum currency, encryption, random number generation.
MSQC602
Physics of Quantum Devices
Credits: 3
Grad Meth: Reg
An introduction to quantum physics with emphasis on topics at the frontiers of research, and developing understanding through exercises.This course aims to build a bridge between natural principles such as light and atoms and a variety of modern applications. This course will provide the student with the necessary physical intuition and background information on quantum physics so that to be able to understand and appreciate a variety of applications in quantum computing such as quantum currency, encryption, random number generation
MSQC603
Principles of Machine Learning
Credits: 3
Grad Meth: Reg
Restriction: Must be in one of the following programs: (Data Science Post-Baccalaureate Certificate, Master of Professional Studies in Data Science and Analytics, or Master of Professional Studies in Machine Learning).
Cross-listed with: DATA603, BIOI603, MSML603.
Credit only granted for: BIOI603, DATA603, MSML603, MSQC603 or CMSC643.
Formerly: CMSC643.
A broad introduction to machine learning and statistical pattern recognition. Topics include: Supervised learning: Bayes decision theory, discriminant functions, maximum likelihood estimation, nearest neighbor rule, linear discriminant analysis, support vector machines, neural networks, deep learning networks. Unsupervised learning: clustering, dimensionality reduction, PCA, auto-encoders. The course will also discuss recent applications of machine learning, such as computer vision, data mining, autonomous navigation, and speech recognition.