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PHYS 440 Big Data Physics 3.0 Credits
This course provides the framework for physics students at all levels to begin interacting with large data sets in physics. Data analysis will be done using Python tools, including standard libraries for machine learning. Practical application of classification and regression techniques for both unsupervised and supervised data are emphasized, in addition to dimensionality reduction techniques and time-domain analysis. An introduction to statistical methods, Bayesian inference, and Markov-chain Monte Carlo methods provide a foundation for application of machine learning tools.
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: PHYS 115 [Min Grade: D] or CS 171 [Min Grade: D]
International Business
http://catalog.drexel.edu/undergraduate/schoolofeconomics/internationalbusiness/
...or 101 CHEM 151 PHYS 151 , 170 , or...450 4.0 INTB 440 4.0 ENGL...
International Business BSBA / Business Administration MBA
http://catalog.drexel.edu/undergraduate/collegeofbusiness/internationalbusinessbsba-mba/
...151 CHEM 151 PHYS 151 PHYS 151 15...EXPERIENCE COOP EXPERIENCE INTB 440 4.0 (UG...
Graphic Design
http://catalog.drexel.edu/undergraduate/collegeofmediaartsanddesign/graphicdesign/
...UNIV A101 1.0 PHYS 175 3.0...460 3.0 VSCM 440 4.0 Free...