PHYS 762 - Applied Machine Learning in Nuclear and Particle Physics (C)

3 cr

Description This one-semester course introduces problem solving in nuclear and particle physics through statistical inference, machine learning (ML) algorithms, and data mining techniques. The course focuses on the application of state-of-the-art ML methods in physics, such as Monte Carlo sampling, regression and classification techniques, deep learning, dimensionality reduction, and data cleaning.
Prerequisites and Corequisites Prerequiste: Select one of the following: PHYS 733, PHYS 761, CSC 547, CSC 586, CSC 588, CSC 722, or CSC 761 at USD or CSC 559 at SDSMT or instructors permission.
Notes Common course with SDSMT and USD.

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