The development of new sensors and experiments providing data at ever-increasing densities and rates has greatly aided research in physics, spanning the scales of galaxies and inspiraling black holes down to bacteria and quarks and leptons. It wouldn’t be an exaggeration to say that physics is awash with data of all kinds.
Beyond efforts to find useful parameterizations of this data, physicists commonly develop predictive computational models to compare with observed data. Once refined, the models themselves provide us with important details about the underlying physical processes, be it the masses of colliding black holes, the interactions between different types of gut bacteria derived from analysis of images of zebrafish, or the fundamental energy of the Higgs boson.
In the data science domain area of physics, you will learn to construct and apply computational models to draw physical insights from a diverse collection of data.
You will take three physics domain core courses and four courses from the electives menu.
Physics Core Courses (all three required)
|PHYS 251||Foundations of Physics I||Fall|
|PHYS 253||Foundations of Physics I||Spring|
|PHYS 290||Foundations of Physics Laboratory||Fall, Winter, Spring|
Physics Electives (choose three in addition to PHYS 391)
|PHYS 391||Physics Experimentation Data Analysis Laboratory||Fall, Winter|
|PHYS 410||Image Analysis with Applications in Physics||Fall|
|PHYS 432||Digital Electronics||Spring|
|PHYS 445||Computational Physics||Spring|
|PHYS 481||Design of Experiments||Spring|
|PHYS 491||Research Project I||Fall, Winter, Spring|
|DSCI 411**||Data Science Capstone|
** Students with a GPA of 3.75 or higher overall in all data science degree courses are eligible.