Fall 2024 Industrial Engineering and Operations Research E4577 section 001

TOPICS IN OPERATIONS RESEARCH

APPLIED RISK ANALYTICS

Call Number 14562
Day & Time
Location
T 5:40pm-8:10pm
303 Seeley W. Mudd Building
Points 1.5
Grading Mode Standard
Approvals Required None
Instructor Amit Arora
Type LECTURE
Method of Instruction In-Person
Course Description

The course focuses on a PRACTICAL study of how to quantify & predict RISK in organizations by using learnings from: Regression analysis; Monte Carlo simulation; Factor analysis; Cohort analysis; Cluster analysis; Time series analysis; Sentiment analysis. Expectation is that incoming students should have a basic understanding of such concepts and statistics. The course will offer meeting & listening to CXO's & top executives from companies who have implemented robust AI & Applied Risk solutions to solve real-world problems in their own industries. 
It will give students a great opportunity to learn practical applications of predictive analytics to solve real business problems

Web Site Vergil
Department Industrial Engineering and Operations Research
Enrollment 31 students (60 max) as of 9:06PM Tuesday, February 4, 2025
Subject Industrial Engineering and Operations Research
Number E4577
Section 001
Division School of Engineering and Applied Science: Graduate
Open To Engineering:Graduate
Note A-Term
Section key 20243IEOR4577E001