Spring 2025 Industrial Engineering and Operations Research E4578 section 001

TOPICS IN OPERATION RESEARCH

Forecasting realworld app

Call Number 14635
Day & Time
Location
R 7:00pm-9:30pm
To be announced
Points 3
Grading Mode Standard
Approvals Required None
Instructors Syed W Haider
Robert Kramer
Type LECTURE
Method of Instruction In-Person
Course Description

A project-based course in Forecasting, predicting a time series into the future, to prepare students for real-world applications including articulating the business case, value creation, problem statement, and the iterative development of solutions including building a data pipeline, exploration, modeling, and visualizations. The course will use Statistical methods, Machine Learning, and Deep Learning with Transformer-based methods to predict a time series. It will use nuggets of signal processing to augment Machine Learning models to characterize and filter orders of dynamics in the time series data.

Web Site Vergil
Department Industrial Engineering and Operations Research
Enrollment 77 students (70 max) as of 6:06PM Thursday, January 2, 2025
Status Full
Subject Industrial Engineering and Operations Research
Number E4578
Section 001
Division School of Engineering and Applied Science: Graduate
Open To Engineering:Graduate
Note DSI Section, Topics Title: Forecasting: A real-world applica
Section key 20251IEOR4578E001