Beginning with students admitted in the fall of 2026, all students pursuing on-ground master's degree programs must complete a university-level experiential learning requirement. This requirement may be fulfilled through the curriculum, co-op, or other work- or industry-integrated learning experiences.
Complete all courses and requirements listed below unless otherwise indicated.
Students should refer to the course numbering table for graduate course leveling.
Data Science Core
A cumulative GPA of 3.000 or higher is required in the following core courses.
| Code | Title | Hours |
|---|---|---|
| Programming with Data | ||
| DS 5110 | Essentials of Data Science | 4 |
| Algorithms | ||
| CS 5800 | Algorithms | 4 |
| or EECE 7205 | Fundamentals of Computer Engineering | |
| Machine Learning | ||
| CS 6140 | Machine Learning | 4 |
| or EECE 5644 | Introduction to Machine Learning and Pattern Recognition | |
| Interdisciplinary Capstone | ||
| DS 5500 | Data Science Capstone | 4 |
Data Science Concentration Options
Complete one of the following concentrations:
- Computer Science—Khoury College of Computer Sciences
- Data Design and Visualization—College of Arts, Media and Design
Program Credit/GPA Requirements
32 total semester hours required
Minimum 3.000 GPA required
Computer Science Concentration—Khoury College of Computer Sciences
| Code | Title | Hours |
|---|---|---|
| Complete 16 semester hours from the following: | 16 | |
| Foundations of Artificial Intelligence | ||
| Reinforcement Learning and Sequential Decision Making | ||
| Database Management Systems | ||
| Pattern Recognition and Computer Vision | ||
| Computer/Human Interaction | ||
| Web Development | ||
| Natural Language Processing | ||
| Information Retrieval | ||
| Data Mining Techniques | ||
| Large-Scale Parallel Data Processing | ||
| Empirical Research Methods | ||
| Fundamentals of Cloud Computing | ||
| Building Scalable Distributed Systems | ||
| Advanced Machine Learning | ||
| Deep Learning | ||
| Special Topics in Artificial Intelligence | ||
| Statistical Methods for Computer Science | ||
| Information Visualization: Theory and Applications | ||
| Special Topics in Database Management | ||
| Special Topics in Data Science | ||
| Thesis | ||
| Master’s Project | ||
| Project | ||
| Optional Co-op | ||
| CS 6964 | Co-op Work Experience | 0 |
| or CS 6954 | Co-op Work Experience - Half-Time | |
| or CS 6955 | Co-op Work Experience Abroad - Half-Time | |
| or CS 6965 | Co-op Work Experience Abroad | |
Data Design and Visualization—College of Arts, Media and Design
| Code | Title | Hours |
|---|---|---|
| Complete 8 semester hours from the following: | 8 | |
| Information Visualization Principles and Practices | ||
| Information Design Critique Seminar | ||
| Visualization Technologies 1: Fundamentals | ||
| Complete 8 semester hours from the following: | 8 | |
| Visual Cognition | ||
| Information Design Theory and Critical Thinking | ||
| Information Design Mapping Strategies | ||
| Computer/Human Interaction | ||
| Web Development | ||
| Information Visualization: Theory and Applications | ||
| Optional Co-op | ||
| EEAM 6964 | Co-op Work Experience | 0 |
| or EEAM 6954 | Co-op Work Experience - Half-Time | |
| or EEAM 6955 | Co-op Work Experience Abroad - Half-Time | |
| or EEAM 6965 | Co-op Work Experience Abroad | |