Academic Coursework Overview
Courses Taken@UW-Madison
Mathematics
- Calculus & Analysis
- MATH 221: Calculus & Analytic Geometry I
- MATH 222: Calculus & Analytic Geometry II
- MATH 234: Calculus–Functions of Several Variables
- MATH 421: Theory of Single Variable Calculus
- MATH 521: Analysis I
- MATH 623: Complex Analysis
- Probability
- MATH/STAT 310: Introduction to Probability & Mathematical Statistics II
- MATH/STAT 431: Introduction to the Theory of Probability
- MATH/STAT/COMP SCI 475: Introduction to Combinatorics
- MATH/STAT/ISYE/OTM 632: Introduction to Stochastic Processes
- Algebra
- MATH 340: Elementary Matrix & Linear Algebra
- MATH 541: Modern Algebra
- Research
- MATH 390: Undergraduate Research - MXM
Statistics
- Applied Statistics & Programming
- STAT 303: R for Statistics I
- STAT 333: Applied Regression Analysis
- STAT 349: Introduction to Time Series
- STAT 371: Introduction to Applied Statistics for Life Sciences
- STAT 424: Statistical Experimental Design
- STAT 451: Machine Learning
Computer Science
- Programming & Data Science
- COMP SCI 200: Programming I
- COMP SCI 220: Data Science Programming I
- COMP SCI 532: Matrix Methods in Machine Learning
Physical Sciences
- Physics
- PHYSICS 103: General Physics I
- PHYSICS 104: General Physics II
- Chemistry
- CHEM 103: General Chemistry I
- CHEM 104: General Chemistry II
Biological Sciences
- Biology
- ZOOLOGY 101: Animal Biology
- ZOOLOGY 102: Animal Biology Laboratory
Courses Taken@Duke(In Progress)
Fall 2025
- STAT 532: Theory of Inference
- STAT 523L: Statistical Programming(*Waived)
- STAT 521L: Predictive Modelling
- STAT 581: Statistical Science Proseminar
- STAT 690: Deterministic Optimization
- STAT 690-1: SQL: Data Querying & Analysis
Spring 2026
- COMPSCI 675D: Intro to Deep Learning
- STA 561D: Probablistic Machine Learning
- STA 602L: Bayesian Statistical Modeling
- STA 640: Causal Inference
- STA 663L: Statistical Computing