BMGT347F

Quantitative Financial Analysis

Prerequisite: BMGT340; must have completed or be concurrently enrolled in BMGT343. Credit only granted for: BMGT347 or BMGT448G. Formerly: BMGT448G. Introduces students to data science for financial applications using an industry-standard programming language. Students will use tools ranging from regression models to machine learning to investigate questions across a variety of areas within finance including asset management, corporate finance and FinTech. The course will illustrate how big data and data analytics can improve financial decision-making by focusing on problems facing finance professionals. Restricted to Quantitative Finance Fellows.

Sister Courses: BMGT347

Past Semesters

2 reviews
Average rating: 2.50

During the Spring 2020 and Spring 2021 semesters, students could choose to take some of their courses pass-fail mid-semester which skews grade data aggregated across multiple semesters.

Average GPA of 2.38 between 28 students*

BMGT347F Grade Distribution+-05101520253035404550556065% of studentsABCDFWother
A-: 17.86%
A: 32.14%
A+: 10.71%
W: 39.29%
* "W"s are considered to be 0.0 quality points. "Other" grades are not factored into GPA calculation. Grade data not guaranteed to be correct.