Program Director
Priyantha Kumarawadu
eecsugradadmit@syr.edu
Description:
The Bachelor of Science in Artificial Intelligence (AI) Science educates artificial intelligence professionals with a rigorous AI program rooted in the computational disciplines. Graduates will be well-equipped for highly technical positions requiring in-depth technical knowledge of AI systems and provides both hardware and software tracks, allowing students to specialize. The program requires 120 credits including the 60-credit liberal arts core, a 23-credit computing core, a 15-credit AI core, 8-credit AI capstone sequence, a 9-credit specialty track, and 6 credits in AI electives.
The programs in AI Science prepare professionals who will adapt to constant changes in technology and who will be leaders in developing the new AI technologies.
AI Science focuses on strong fundamentals in computing and digital design, machine learning, knowledge representation and reasoning, and large language models. Syracuse’s program weaves together an emphasis on fundamental principles with new developments in AI, producing graduates prepared either to begin careers or to pursue advanced studies in the field.
With this program you will have opportunities to learn about:
- AI Systems with Reasoning Capabilities
- Deep learning and neural networks
- Large language models and Natural language processing
- Programming with AI
- Hardware considerations for AI (hardware concentration)
- Data mining and computer vision (software concentration)
- Understanding of the limitations of today’s AI systems and how researchers are working to overcome them
- Innovative thinking so you can design the next generation of AI software or hardware systems
- The mathematics behind AI algorithms
- Problem solving, independent thinking and team collaboration in developing a AI systems
Programs Requirements
The BS degree in Artificial Intelligence Science requires a minimum of 120 credits. The requirements are divided into a general education section, a mathematics section, and a major section.
Course List | Code | Title | Credits |
| 60 |
| Logic | |
| AI Ethics and Governance | |
| AI & Humanity: Charting Possible Futures | |
| General Physics I and General Physics Laboratory I | |
| Calculus I | |
| Calculus II | |
| First Course in Linear Algebra | |
| Introduction to Probability and Statistics | |
| ECS 101 | Introduction to Engineering and Computer Science | 3 |
| CIS 151 | Fundamentals of Computing and Programming | 3 |
CSE 261 & CSE 262 | Digital Logic Design and Digital Logic Design Laboratory | 4 |
| CSE 283 | Introduction to Object-Oriented Design | 3 |
| or CIS 252 | Elements of Computer Science |
| CIS 375 | Introduction to Discrete Mathematics | 3 |
| CIS 351 | Data Structures | 3 |
| CIS 477 | Introduction to Analysis of Algorithms | 3 |
| ASE 309 | Technical Fundamentals of Artificial Intelligence | 3 |
| ASE 310 | AI Experiential Programming | 3 |
| ASE 465 | Introduction to Machine Learning | 3 |
| ASE 469 | Artificial Intelligence Algorithms | 3 |
| CIS 468 | Natural Language Processing | 3 |
| ASE 453 | Artificial Intelligence Capstone 1 | 3 |
| ASE 454 | Artificial Intelligence Capstone 2 | 3 |
| ASE 491 | AI Seminar | 2 |
| |
| Systems and Network Programming | |
| Computer Architecture | |
| AI Hardware Design Fundamentals | |
| Automata and Computability | |
| Multiagent Systems: Concepts and Programming | |
| Digital Audio Signal Processing | |
| Image and Video Processing | |
| Minds and Machines | |
| Logic and Language | |
| Mathematical Logic | |
| Modal Logic | |
| Independent Study | |
| Honors Capstone Project | |
| 9 |
Hardware Concentration
Course List | Code | Title | Credits |
| CSE 384 | Systems and Network Programming | 3 |
| CSE 381 | Computer Architecture | 3 |
| ASE 460 | AI Hardware Design Fundamentals | 3 |
| Total Credits | 9 |
Software Concentration
Course List | Code | Title | Credits |
| ELE 453 | Image and Video Processing | 3 |
| ASE 463 | Data Mining | 3 |
| CIS 473 | Automata and Computability | 3 |
| Total Credits | 9 |
Intra-University Transfer
Students who wish to transfer into any program within the College of Engineering and Computer Science from another school or college within the University should have a strong record of achievement and demonstrated success in key technical courses. Specifically, it is critical for the applicant to have proven their ability to excel in college-level calculus (by completing at least one of MAT 295 Calculus I, MAT 296 Calculus II, or MAT 397 Calculus III with a grade of B- or better) and science (by completing at least one set of PHY 211 General Physics I/PHY 221 General Physics Laboratory I or CHE 106 General Chemistry Lecture I/CHE 107 General Chemistry Laboratory I with a grade of B- or better). Students who wish to major in Artificial Intelligence Science must also complete CIS 252 Elements of Computer Science or CSE 283 Introduction to Object-Oriented Design with a grade of at least a B.