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Courses - Fall 2024
MSQC
Quantum Computing
Open Seats as of
07/19/2024 at 10:30 PM
MSQC601
Mathematics and Methods of Quantum Computing
Credits: 3
Grad Meth: Reg
This course will provide the student with the necessary mathematical tools and background knowledge to understand, model, and conceptualize quantum computing and its building blocks and systems. We shall review concepts of computation and how they translate to the microscopic world.
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.
The lecture may be conducted online some weeks and in person other weeks. Please see ELMS for Class meeting details.