ASRM 499

Spring 2022 All Classes

All Classes

Topics in Actuarial Science

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Credit: 1 TO 4 hours.

Covers special topics in actuarial science.

1 to 4 undergraduate hours. 1 to 4 graduate hours. Approved for Letter and S/U grading. May be repeated. Prerequisite: Consent of instructor.

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ASRM 499 class schedule data for spring 2022
CRN	Type	Section	Time	Day	Location	Instructor	Section Details
73113	Lecture-Discussion	GR	11:00AM -12:20PM	TR	1090 Lincoln Hall	Freiji, C	Part of Term: 1 Date Range: 01/18/22-05/04/22 Credit: 4 hours Section Title: Statistics for Risk Modeling Section Info: Restricted to graduate students in the Actuarial Science Program. This section meets concurrently with ASRM 499 SRM but requires additional work for the fourth credit. Restriction(s): Restricted to Graduate - Urbana-Champaign. Restricted to MS:App Mth-Actuarial Sci -UIUC or MS: Actuarial Science - UIUC.
68706	Lecture-Discussion	PA	2:00PM -3:20PM	TR	245 Altgeld Hall	Jing, X	Part of Term: 1 Date Range: 01/18/22-05/04/22 Credit: 3 hours Section Title: Predictive Analytics Section Info: Prerequisite: ASRM 401 or STAT 410, plus basic knowledge of coding. Experience with R and LaTeX is a plus but not required. This course will introduce basic statistical and machine learning tools to solve problems in actuarial science and quantitative finance and show how to communicate results to a general audience. We will introduce several key problems in actuarial science and quantitative finance, show standard mathematical models for these problems and illustrate how statistical and machine learning tools can help to improve existing solutions for these problems. Whereas some courses focus on applying statistical tools in different settings, the goal of this course is to give insight into these problems and be critical to possible statistical solutions. Restriction(s): Restricted to Actuarial Science major(s).
72802	Lecture-Discussion	S13	11:00AM -12:20PM	TR	1090 Lincoln Hall	Freiji, C	Part of Term: 1 Date Range: 01/18/22-05/04/22 Credit: 3 hours Section Title: Statistics for Risk Modeling Section Info: Prerequisite: ASRM 450/Stat 420. This course will introduce students to the theory behind supervised and unsupervised data analysis techniques. Topics will cover: the theory behind generalized linear regression (link functions, parameter estimation, testing of hypothesis and model selection criteria); Time series (ARIMA models); Decision trees (Regression and Classification Techniques CART); Data reduction method using principle components; Unsupervised learning technique using cluster analysis. This course will prepare students for the SOA Exam SRM. Restriction(s): Restricted to Actuarial Science major(s).