Complete all courses listed below unless otherwise indicated. Also complete any corequisite labs, recitations, clinicals, or tools courses where specified and complete any additional courses needed beyond specific college and major requirements to satisfy graduation credit requirements.
Universitywide Requirements
All undergraduate students are required to complete the Universitywide Requirements.
NUpath Requirements
All undergraduate students are required to complete the NUpath Requirements.
Artificial Intelligence Major Requirements
| Code | Title | Hours |
|---|---|---|
| Computer Science Overview | ||
| CS 1200 | First Year Seminar | 1 |
| or INPR 1000 | First-Year Interdisciplinary Seminar | |
| CS 1210 | Professional Development for Khoury Co-op | 1 |
| Fundamental Courses | ||
| All students can take a self-assessment to attempt to place out of CS 2000 and CS 2001. Students who place out of CS 2000 and CS 2001 will instead substitute 4-5 semester hours of CS, CY, or DS coursework at the 3000 level or higher not otherwise required in the degree. | ||
| CS 1800 | Discrete Structures | 4 |
| CS 2000 and CS 2001 | Introduction to Program Design and Implementation and Lab for CS 2000 | 5 |
| CS 2100 and CS 2101 | Program Design and Implementation 1 and Lab for CS 2100 | 5 |
| Computer Science Required Courses | ||
| CS 2700 and CS 2701 | Data Structures and Analysis and Lab for CS 2700 | 5 |
| CS 3200 | Introduction to Databases | 4 |
| CS 3100 and CS 3101 | Program Design and Implementation 2 and Lab for CS 3100 | 4 |
| or CS 3520 | Programming in C++ | |
| Artificial Intelligence Electives | ||
| Complete three of the following: | 12 | |
| Principles of Artificial Intelligence | ||
| Natural Language Processing | ||
| AI Policy: Machine Learning, Markets, and Morals | ||
| Engineering LLM-Integrated Systems | ||
| Information Retrieval | ||
| AI Security and Privacy | ||
| Artificial Intelligence Required Courses | ||
| DS 3000 | Mathematical Foundations of Artificial Intelligence | 4 |
| DS 3500 | Advanced Programming with Data | 4 |
| DS 4200 | Information Presentation and Visualization | 4 |
| DS 4300 | Large-Scale Information Storage and Retrieval | 4 |
| DS 4400 | Machine Learning | 4 |
| DS 4420 | Advanced Machine Learning | 4 |
| or DS 4440 | Modern Neural Networks | |
| Presentation Requirement | ||
| Complete one of the following: | 4 | |
| Public Speaking | ||
| Business and Professional Speaking | ||
| Persuasion and Rhetoric | ||
| Communication and Storytelling | ||
| Improvisation | ||
| Introduction to Acting | ||
| Dynamic Presence: Theatre Training for Effective Interpersonal Interactions | ||
| Acting for the Camera | ||
| Mathematics Foundations | ||
| MATH 1341 | Calculus 1 for Science and Engineering | 4 |
| MATH 1342 | Calculus 2 for Science and Engineering | 4 |
| MATH 2331 | Linear Algebra | 4 |
| MATH 3081 | Probability and Statistics | 4 |
| Artificial Intelligence and Ethics | ||
| PHIL 1145 | Technology and Human Values | 4 |
| Khoury Approved Electives | ||
| With advisor approval, directed study, research, project study, and appropriate graduate-level courses may also be taken as upper-division electives. | ||
| Complete 4 semester hours from within the following options: | 4 | |
CS 2300 or higher, except CS 5010 | ||
CY 2000 or higher, except CY 4930 | ||
DS 2500 or higher, except DS 4900 | ||
| Digital, Analytics, Technology, and Automation Research Practicum | ||
| Embedded Design: Enabling Robotics | ||
| Fundamentals of Digital Design and Computer Organization and Lab for EECE 2322 | ||
| Artificial Intelligence Related Electives in Other Units | ||
| Complete one of the following: | 4 | |
| Information Design Studio 1: Principles | ||
| Information Design History | ||
| Research Methods for Design | ||
| Visualization Technologies 1: Fundamentals | ||
| Information Design Studio 2: Dynamic Mapping and Models | ||
| Empirical Research Methods | ||
| Statistics for Economists | ||
| Applied Econometrics | ||
| Computer Vision | ||
| Data Visualization | ||
| Introduction to Machine Learning and Pattern Recognition | ||
| Biostatistics | ||
| Game Design and Analysis | ||
| Data-Driven Game Design | ||
| Introduction to Health Informatics and Health Information Systems | ||
| Data Management in Healthcare | ||
| Personal Health Interface Design and Development | ||
| Evaluating Health Technologies | ||
| Data Mining for Engineering Applications | ||
| Calculus 3 for Science and Engineering | ||
| Statistics and Stochastic Processes | ||
| Business Statistics | ||
| Data Management for Business | ||
| Marketing Research | ||
| Marketing Analytics | ||
| Information Ethics | ||
| AI Ethics | ||
| Statistics in Psychological Research | ||
| Cognition | ||
Writing Requirement
| Code | Title | Hours |
|---|---|---|
| College Writing | ||
| ENGW 1111 | First-Year Writing | 4 |
| Advanced Writing in the Disciplines | ||
| ENGW 3302 | Advanced Writing in the Technical Professions | 4 |
| or ENGW 3315 | Interdisciplinary Advanced Writing in the Disciplines | |
Required General Electives
| Code | Title | Hours |
|---|---|---|
| Complete 28 semester hours of general electives. | 28 | |
NUpath Requirements Satisfied
- Engaging with the Natural and Designed World
- Conducting Formal and Quantitative Reasoning
- Analyzing and Using Data
- Writing in the First Year
- Advanced Writing in the Disciplines
- Writing-Intensive in the Major
- Demonstrating Thought and Action in a Capstone
Integrating Knowledge and Skills Through Experience is satisfied through co-op.
Program Requirement
132 total semester hours required