Coursework

core

Causal Inference with Modern Machine Learning Methods

DSO 603 USC Marshall Graduate (Doctoral) Fall 2025 Yingying Fan

Doctoral-level introduction to causal inference at the intersection of machine learning, focusing on theoretical foundations and recent research developments.

ISE-547: Applied Generative AI for Enterprises

ISE-547 USC Viterbi Graduate

Master's level course on Applied Generative Artificial Intelligence for Enterprises at USC.

Sample Coursework Project

BUAD 311 USC Marshall Undergraduate

This is a sample coursework project to demonstrate the new Coursework tab.

Generalized Linear Mixed Models

STA6640 Yonsei University Graduate

Theory and data analysis methods for Generalized Linear Mixed Models (GLMM), extending regression to exponential families and random effects.

Machine Learning for/with Mixed-Integer Optimization

ISE 617 / CSCI 617 USC Viterbi Graduate (Doctoral) Spring 2026 Andres Gomez & Bistra Dilkina

Ph.D. level course exploring the intersection of Machine Learning and Mixed-Integer Optimization, covering how MIO enhances ML and how ML improves MIO solvers.

Modern Statistical Inference

DSO 699 USC Marshall Graduate Fall 2023 Adel Javanmard

Ph.D. level course on Modern Statistical Inference, focusing on high-dimensional settings and statistical learning theory.

elective