PS 590

Fall 2025

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Credit: 2 TO 12 hours.

Research in selected topics by arrangement with the instructor.

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CRN Type Section Time Day Location Instructor Section Details
10195
Independent Study
ARRANGED
n.a.
Location Pending
Part of Term:
1
Date Range:
08/25/25-12/10/25
Special Approval:
Instructor Approval Required
Section Info:
This section is a placeholder and cannot be used for registration. To register, please forward the faculty member's email approval to: ps-gradoffice@illinois.edu. You will then be provided a CRN for the course registration.
Restriction(s):
Restricted to Graduate - Urbana-Champaign.
26048
Lecture-Discussion
A
9:30AM -11:50AM
T
404 David Kinley Hall
Vasselai, F
Part of Term:
1
Date Range:
08/25/25-12/10/25
Credit:
4 hours
Section Title:
Intro Supervised Mach Learning
Section Info:
Title: Intro to Supervised Machine Learning. Course will be taught by Professor Fabricio Vasselai. This course will cover the fundamentals of Supervised Machine Learning (SML), with an applied focus and geared towards Political and Social Scientists. Students will be introduced to key prediction techniques like k-nearest neighbors, naïve bayes classifier, regularized linear and non-linear regression, decision trees, random forests, SVM and a variety of deep neural networks. Naturally, the course will also cover parameter optimization and also how to evaluate SML model predictions using different types of cross-validation (Monte Carlo, leave-k-out, block) and with different metrics. The course ends with a discussion of bias, fairness and trustworthiness in SML and how to use interpretable / explanation methods to address such issues. Note that the course will cover some of the crucial mathematical foundations behind each technique, but a lot of the focus will be both on having the students learn the critical concepts and develop deep intuitions about the techniques, and on the application of each method using R programming language. Prerequisites: PS 530 and PS 531 (or equivalent); being able to read/write R code, including loops and custom functions (note: online review practice will be made available).
Restriction(s):
Restricted to Graduate - Urbana-Champaign.
Restricted to PHD:Political Science -UIUC.
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