Program Contact: Christian Duncan 203-582-3817
The impact of artificial intelligence in the last several years is readily apparent, as people and companies across a variety of industries adopt AI tools to improve efficiency and productivity. Society needs graduates who not only have a strong understanding of how to use AI effectively, but also have a deep knowledge of its theoretical underpinnings. The Artificial Intelligence and Computing program provides students with a strong foundation in artificial intelligence, computer science and software development. Students take courses addressing the theoretical and scientific foundations of artificial intelligence, the ethical questions surrounding its creation and usage, and its applications both inside and outside of computing. In a rapidly changing field, Artificial Intelligence and Computing graduates are equipped to independently identify, learn and apply new concepts.
The BS in Artificial Intelligence and Computing program requires a minimum of 120 credits for degree completion.
Note: A minimum grade of C- is required for all computer science course prerequisites unless otherwise stated.
Within the policies of the School of Computing & Engineering, the Artificial Intelligence and Computing program enforces credit limits during the academic terms. Exceeding 18 credits in the fall or spring semesters, 4 credits in the January term, or 10 credits in each summer term requires the approval of the dean’s office.
Please see footnotes for additional information.
| Code | Title | Credits |
|---|---|---|
| University Curriculum | 46 | |
| AI & Computing Core Requirements | ||
| CSC 110 & 110L | Programming and Problem Solving and Programming and Problem Solving Lab | 4 |
| CSC 111 & 111L | Data Structures and Abstraction and Data Structures and Abstraction Lab | 4 |
| CSC 150 | AI for Everyone | 3 |
| SER 120 & 120L | Object-Oriented Design and Programming and Object-Oriented Design and Programming Lab | 4 |
| CSC 215 | Algorithm Design and Analysis | 3 |
| SER 225 | Introduction to Software Development | 3 |
| CSC 325 | Database Systems | 3 |
| CSC 350 | Artificial Intelligence | 3 |
| CSC 355 | Machine Learning | 3 |
| CSC/SER Electives 200 or higher (Take 3 credits of CSC/SER elective courses numbered 200 or higher) | 3 | |
| CSC/SER Electives 300 or higher (Take 6 credits of CSC/SER elective courses numbered 300 or higher) | 6 | |
| Take one course from: | 3 | |
| Natural Language Processing | ||
| Generative AI | ||
| Senior Project or Senior Thesis - Choose one pair | 4-6 | |
| Senior Project I and Senior Project II | ||
| Senior Thesis I and Senior Thesis II | ||
| ENR 395 | Professional Development Seminar | 1 |
| MA 285 | Applied Statistics | 3 |
| Origins and Applications of AI Electives (Take 6 credits from list) 1 | 6 | |
| Required courses counting toward the University Curriculum | ||
| Computing: Multidisciplinary Approach | ||
| Calculus of a Single Variable | ||
or MA 151 | Calculus I | |
| Introduction to Discrete Mathematics (CSC 205) | ||
| Ethics and Artificial Intelligence | ||
| Open Electives | 16-18 | |
| Total Credits | 118-122 | |
Course plans are subject to change. Course availability, potential transfer credits, and course prerequisite completion may influence the final course schedule for each program.
| First Year | ||
|---|---|---|
| Fall Semester | Credits | |
| CSC 110 & 110L |
Programming and Problem Solving and Programming and Problem Solving Lab |
4 |
| MA 140 | Pre-Calculus (UC Personal Inquiry 2) | 3 |
| FYS 101 | First-Year Seminar (UC Foundations Inquiry) | 3 |
| EN 101 | Introduction to College-Level Reading And Writing (UC Writing) | 3 |
| CSC 150 | AI for Everyone | 3 |
| Credits | 16 | |
| Spring Semester | ||
| CSC 111 & 111L |
Data Structures and Abstraction and Data Structures and Abstraction Lab |
4 |
| SER 120 & 120L |
Object-Oriented Design and Programming and Object-Oriented Design and Programming Lab |
4 |
| MA 205 | Introduction to Discrete Mathematics (CSC 205) (UC Math) | 3 |
| EN 102 | Reading, Writing, & Research In College and Beyond (UC Writing 2) | 3 |
| Credits | 14 | |
| Second Year | ||
| Fall Semester | ||
| CSC 215 | Algorithm Design and Analysis | 3 |
| SER 225 | Introduction to Software Development | 3 |
| CSC 105 | Computing: Multidisciplinary Approach (UC Personal Inquiry 2) | 3 |
| MA 141 | Calculus of a Single Variable (UC Personal Inquiry 2) | 3 |
| University Curriculum Science and Lab | 4 | |
| Credits | 16 | |
| Spring Semester | ||
| CSC 350 | Artificial Intelligence | 3 |
| PL 255 | Ethics and Artificial Intelligence (UC Humanities) | 3 |
| MA 285 | Applied Statistics | 3 |
| University Curriculum course | 3 | |
| University Curriculum course | 3 | |
| Credits | 15 | |
| Third Year | ||
| Fall Semester | ||
| CSC 325 | Database Systems | 3 |
| CSC/SER 2xx Elective | 3 | |
| Origins/Applications of AI Elective | 3 | |
| University Curriculum course | 3 | |
| Open Elective or UC Intercultural course | 3 | |
| ENR 395 | Professional Development Seminar | 1 |
| Credits | 16 | |
| Spring Semester | ||
| CSC 355 | Machine Learning | 3 |
| CSC/SER 3xx Elective | 3 | |
| Origins/Applications of AI Elective | 3 | |
| University Curriculum course | 3 | |
| University Curriculum course | 3 | |
| Credits | 15 | |
| Fourth Year | ||
| Fall Semester | ||
| CSC 491 or CSC 493 |
Senior Project I or Senior Thesis I |
1-3 |
| CSC 351 or CSC 352 |
Natural Language Processing or Generative AI |
3 |
| UC Integrative Capstone | 3 | |
| Open Elective | 3 | |
| Open Elective | 3 | |
| Credits | 13-15 | |
| Spring Semester | ||
| CSC 492 or CSC 494 |
Senior Project II or Senior Thesis II |
3 |
| CSC/SER 3xx Elective | 3 | |
| Open Elective | 3 | |
| Open Elective | 3 | |
| Open Elective | 3 | |
| Credits | 15 | |
| Total Credits | 120-122 | |
Student Outcomes
Graduates of the program will have an ability to:
- Analyze a complex computing problem and apply principles of computing and other relevant disciplines to identify solutions.
- Design, implement and evaluate a computing-based solution to meet a given set of computing requirements at the confluence of computer science and artificial intelligence.
- Communicate effectively in a variety of professional contexts.
- Recognize professional responsibilities and make informed judgments in computing and artificial intelligence practice based on legal and ethical principles.
- Function effectively as a member or leader of a team engaged in activities appropriate to the program’s discipline.
- Apply computer science theory and software development fundamentals to produce computing-based solutions.
Program Educational Objectives
Within four to seven years of graduation, graduates of the Artificial Intelligence and Computing BS program are expected to:
- Apply advanced computer science and artificial intelligence knowledge and skills.
- Communicate complex ideas and problems to a professional audience.
- Demonstrate ethical behavior and capacity for finding computing and AI solutions that consider both the technical and social consequences of their work.
- Demonstrate leadership and mentorship, and contribute to their profession and community.
- Pursue intellectual, personal, and professional development.
Admission Requirements: School of Computing & Engineering
The requirements for admission into the undergraduate School of Computing & Engineering programs are the same as those for admission to Quinnipiac University.
Admission to the university is competitive, and applicants are expected to present a strong college prep program in high school. Prospective first-year students are strongly encouraged to file an application as early in the senior year as possible, and arrange to have first quarter grades sent from their high school counselor as soon as they are available.
For detailed admission requirements, including required documents, please visit the Admissions page of this catalog.