| Call Number | 15259 |
|---|---|
| Day & Time Location |
T 7:00pm-9:30pm 330 Uris Hall |
| 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, with the aim 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 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 | 12 students (60 max) as of 10:06AM Sunday, April 28, 2024 |
| Subject | Industrial Engineering and Operations Research |
| Number | E4574 |
| Section | 001 |
| Division | School of Engineering and Applied Science: Graduate |
| Campus | Morningside |
| Section key | 20233IEOR4574E001 |