PHYS 398 MLA - Data Analysis & Machine Learning Applications

Spring 2022

Soph/Junr Special Topics PhysPHYS398MLA69342LEC21500 - 1650 M  222 Loomis Laboratory Mark Neubauer

Official Description

Topical offerings of technical interest, skills, and knowledge in physics, and its practice, intended to augment the existing curriculum at the intermediate level. Course Information: Approved for Letter and S/U grading. May be repeated in separate terms up to 12 hours if topics vary. Prerequisite: See Class Schedule or departmental course information for topics and prerequisites. For students with sophomore or junior standing.

Section Description

DATA ANALYSIS & MACHINE LEARNING APPLICATIONS In this course, you will learn the fundamentals of how to analyze and interpret scientific data and apply modern machine learning tools and techniques to problems such as classification and regression. . Some knowledge of python preferred but not required. Prerequisites: Credit or Concurrent Registration: MATH 285; Credit for PHYS 225 and PHYS 325