Master of Applied Science in Data Science with Applied Artificial Intelligence
At least nine credit hours must be taken of 400- or 500-level CS or CSP courses and nine credit hours of 400- or 500-level MATH courses.
| Code | Title | Credit Hours |
|---|---|---|
| Core Courses | (18) | |
| MATH 564 | Regression | 3 |
| or MATH 563 | Mathematical Statistics | |
| MATH 569 | Statistical Learning | 3 |
| or CS 584 | Machine Learning | |
| COM 523 | Communicating Science | 3 |
| CSP 571 | Data Preparation and Analysis | 3 |
| MATH 546 | Introduction to Time Series | 3 |
| Select a minimum of one course from the following: | 3 | |
| Big Data Technologies | 3 | |
| Advanced Database Organization | 3 | |
| Data-Intensive Computing | 3 | |
| Required Applied AI Courses | (9) | |
| CS 585 | Natural Language Processing | 3 |
| CS 512 | Computer Vision | 3 |
| CS 577 | Deep Learning | 3 |
| Elective Applied AI Courses | (3) | |
| Select one course from | 3 | |
| Artificial Intelligence in Business | 3 | |
| Advanced Artificial Intelligence | 3 | |
| Applied Artificial Intelligence Programming | 3 | |
| Introduction to Robotics | 3 | |
| Robotics | 3 | |
| Electives | (3) | |
| Select one course from | 3 | |
| Data Driven Modeling | 3 | |
| Bayesian Computational Statistics | 3 | |
| Data Mining | 3 | |
| Database Organization | 3 | |
| Introduction to Algorithms | 3 | |
| Total Credit Hours | 33 | |
