Tepper · MS in Business Analytics
MS in Business Analytics Math Skills Workshop
Course I built
The math incoming MS in Business Analytics students need before the quantitative core begins.
A workshop I developed for incoming MS in Business Analytics students in Summer 2026. The goal is for students to start the program's quantitative courses with the mathematics already in place, so they are not learning it at the same time as the statistics.
Topics
- Algebra fundamentals and functions
- Calculus for analytics: derivatives, optimization, and gradient descent
- Linear algebra for data analytics: matrices, eigenvalues, least squares, PCA, and PageRank
- Descriptive statistics
- Probability foundations
- Statistical inference: sampling distributions, confidence intervals, and hypothesis tests
How the course works
Each module ends where an analytics course picks up. Calculus ends with gradient descent and the sigmoid. Linear algebra ends with the normal equations, PCA, and PageRank. Probability works through a fraud alert that is 99% sensitive and still right only 9% of the time at a 0.5% base rate.
I wrote the scope and sequence with the MS in Business Analytics core faculty, working backward from what their courses need. Before recording, I checked every equation symbolically.
How the course developed
A self-paced online course for incoming MS in Business Analytics students, built with Tepper's learning technologies team between December 2025 and August 2026. I recorded every lesson, about thirty short videos across six modules, each pairing slides with worked problems written out by hand.
Offerings
- Summer 2026
Incoming MS in Business Analytics students take the workshop on Canvas.