Financial Data Science I

Course Number: 46921

The first in a two-course sequence covering methods of extracting useful information from raw financial data. Focus is placed on fundamental tools of statistical inference useful for fitting models to financial data, including those with complex multivariate form. Topics include linear models, nonparametric models, parameter estimation and uncertainty quantification. Methods are taught using the Python programming language. Non-MSCF students may not take this course without written permission from the instructor. To be eligible, you must be a BSCF student, or a graduate student enrolled in an MSCF participating college (Dietrich, Heinz, Tepper or Mellon). PhD students with relevant research may also be eligible.

Concentration: Statistics / Data Science
Semester(s): Mini 1
Required/Elective: Required
Prerequisite(s): None