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Quantitative Preparation

A strong quantitative background will serve as a helpful foundation for the Master’s in Asset Management program. Courses in multivariable calculus, linear or matrix algebra, microeconomic theory, probability and statistics, and computer programming are not required for admission, but exposure to the subject matter through academic or supplemental study will provide a highly beneficial background for the curriculum. While pre-admission coursework in these areas is encouraged, we admit candidates from a wide range of academic backgrounds and offer a Summer Self-Study program to incoming students who have not had exposure to this subject matter prior to matriculation.

Summer Self-Study Program

Admitted students often ask what they can do to accurately assess and/or strengthen their level of quantitative preparedness prior to starting the program. The Master's in Asset Management program director has crafted a Summer Self-Study program for enrolled students, comprised of a list of online courses specifically designed to help students prepare for the academic rigor of the Asset Management program. Offered at the beginning of the summer prior to the start of the program, this set of online coursework can serve as subject matter review for students who have already taken this coursework, or as a way for students with less previous quantitative coursework to gain critical exposure before starting classes.

For reference, the following online coursework was selected for the Master's in Asset Management Class of Summer Self-Study program:

DataCamp Python Fundamentals (15 hours) 

DataCamp Statistics Fundamentals with Python (20 hours) 

DataCamp Time Series with Python (20 hours) 

Coursera Linear Algebra (18 hours) 

Coursera Multivariate Calculus (17 hours) 

Please note that the admissions committee does not expect you to complete these courses prior to submitting your application to the Master’s in Asset Management program. We are offering this course detail as a tool to measure your current quantitative skillset in comparison to the current class of Asset Management students at matriculation.