ASRM 455

Fall 2025 All Classes

All Classes

Credit: 3 OR 4 hours.

Emphasizes techniques of predictive analytics and introductory applications to actuarial science, finance, and economics. Gives an overview of the different statistical learning methods and algorithms that can be employed to discover useful information from datasets, to explain how to build a predictive model using computational software packages (R and Python), and to effectively communicate the results in a scientific report. Topics include identifying the business problem, data preparation, data visualization, model building processes (generalized linear models, decision trees, cluster and principal component analyses, etc.), model selection, refinement, and validation.

3 or 4 undergraduate hours. 3 or 4 graduate hours. Prerequisite: ASRM 401 or STAT 200 or STAT 361.

ASRM 455 class schedule data for fall 2025
CRN Type Section Time Day Location Instructor Section Details
77355
Lecture-Discussion
GP
3:00PM -4:20PM
MW
32 Psychology Building
Jing, X
Part of Term:
1
Date Range:
08/25/25-12/10/25
Credit:
4 hours
Restriction(s):
Restricted to Graduate - Urbana-Champaign. Restricted to MS:App Mth-Actuarial Sci -UIUC, MS: Actuarial Science - UIUC, or MS:PA Risk Mgmt - UIUC.
77354
Lecture-Discussion
UP
3:00PM -4:20PM
MW
32 Psychology Building
Jing, X
Part of Term:
1
Date Range:
08/25/25-12/10/25
Credit:
3 hours
Restriction(s):
Restricted to Actuarial Science major(s).
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