Minor in Applications of Artificial Intelligence
The Applications of AI Minor is designed to equip students across all disciplines at Embry-Riddle Aeronautical University with essential AI literacy and practical competencies. Through a curriculum that spans applications in education, industry, and research, students develop the ability to apply core AI methods responsibly and effectively. The program also emphasizes ethical awareness, privacy considerations, and the importance of human oversight, preparing students to engage thoughtfully with AI in their academic and professional contexts. The 15-credit minor in Applications of AI advances this objective through foundational courses (9 credits) open to all students, complemented by electives (6 credits) aligned with diverse majors.
Some majors may not be eligible to pair with this minor. See the Minor Restrictions list for details.
Daytona Beach Minor Requirements
| Core Requirements | 9 | |
| Electives | 6 | |
| Total Credits | 15 | |
Core Requirements
| HUMN 431 | Ethics and Artificial Intelligence | 3 |
| DSCI 330 | Applied Generative AI | 3 |
| Choose One of the Following: | 3 | |
| Statistics for Data Science | ||
| Introduction to Data Science | ||
| Probability and Statistics | ||
| Business Statistics | ||
| Meteorological Statistics and Data Analysis | ||
| Total Credits | 9 | |
Electives
| Choose 2 of the following courses: | ||
| ASCI 214 | Aviation Networks and Cybersecurity | 3 |
| CESC 440 | Autonomous Vehicle Design | 3 |
| CIVE 460 | Applied Data Science and Numerical Methods in Civil Engineering | 3 |
| CPSC 455 | Artificial Intelligence | 3 |
| BUAN 232 | Techniques in Business Analytics | 3 |
| DSCI 244 | Data Acquisition and Manipulation | 3 |
| DSCI 312 | Machine Learning | 3 |
| DSCI 390 | Research Project in Industrial Mathematics | 3 |
| DSCI 412 | Data Visualization | 3 |
| DSCI 440 | Data Mining | 3 |
| ELEC 311 | Robotics and Autonomous Systems I | 3 |
| or MECH 371 | Robotic Technologies for Uncrewed Systems | |
| MATH 360 | Mathematical Modeling and Simulation I | 3 |
| MATH 488 | Data-driven Numerical Methods for Differential Equations | 3 |
| MMIS 320 | Business Information Systems | 3 |
| Total Credits | 6 | |