ASRM 455

Fall 2026 All Classes

All Classes

Predictive Analytics

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.

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ASRM 455 class schedule data for fall 2026
	Status		CRN	Type	Section	Time	Day	Location	Instructor	Section Details
			77355	Lecture-Discussion	GP	3:00PM -4:20PM	MW	3101 Sidney Lu Mech Engr Bldg	Jing, X	Availability: CrossListOpen (Restricted) Part of Term: 1 Date Range: 08/24/26-12/09/26 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	3101 Sidney Lu Mech Engr Bldg	Jing, X	Availability: Closed Part of Term: 1 Date Range: 08/24/26-12/09/26 Credit: 3 hours Restriction(s): Restricted to Actuarial Science major(s).