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 |