Course Descriptions and Schedule
Please note that course schedules may be amended due to low enrollment, faculty availability, and/or other factors.
MSDS 454-DL : Advanced Modeling Techniques
Description
This advanced modeling course is divided into two major sections. The first section concerns theory and application of stochastic processes, including Markov processes. The second section concerns Bayesian statistics, including Bayesian belief modeling. Throughout the course, students explore applied probability models that represent business processes in graphs or networks. Students execute simulation experiments, both discrete-event and process simulations. This is a case study and project-based course with an extensive programming component.
Prerequisites: (1) MSDS 420-DL Database Systems and Data Preparation or CIS 417 Database Systems Design and Implementation and (2) MSDS 422-DL Practical Machine Learning or CIS 435 Practical Data Science Using Machine Learning.
| Spring 2021 | ||||
| Start/End Dates | Day(s) | Time | Building | Section |
| 03/29/21 - 06/06/21 | Optional Sync W | 7 – 9:30 p.m. | 55 | |
| Instructor | Course Location | Status | CAESAR Course ID | |
| Bhatti, Chad | Online | Open | ||