Artificial Intelligence, M.S.A.I.

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Bellini College of Artificial Intelligence, Cybersecurity, and Computing (AI)

Department of Artificial Intelligencer, Cybersecurity, and Computing

Major Contacts, Deadlines, and Delivery Information

This major shares a core with the Cybersecurity, M.S.C.Y.S.

The Master of Science in Artificial Intelligence (M.S.A.I.) provides comprehensive training in foundational computer science and artificial intelligence concepts while emphasizing practical applications and real-world problem-solving. Designed specifically for students without an undergraduate degree in Computer Science or Computer Engineering, the program equips graduates with the technical skills necessary to transition into AI-focused roles across various industries. The M.S.A.I. is available in both in-person and online formats, offering flexibility to accommodate diverse learning needs. Due to the interdisciplinary nature of AI and the diverse applications it encompasses, students are encouraged to work closely with the Graduate Director to develop a cohesive plan of study tailored to their individual goals. Applicants with prior computing backgrounds are advised to consider the M.S. in Computer Science program or the AI Graduate Certificate for a more advanced pathway.

Major Research Areas:
Machine learning (ML), neural networks, deep learning, natural language processing (NLP), computer vision, robotics and autonomous systems, knowledge representation and reasoning, ethics and policy in AI, AI tools and frameworks, AI in healthcare, finance, education, marketing, and other industries

Admission Information

Must meet University Admission and English Proficiency requirements as well as requirements for admission to the major, listed below.

Three letters of recommendation.
Statement of purpose.
Resume.
PDF of unofficial transcripts.
PDF of English proficiency, if needed.
Evidence of mathematics, problem-solving, and quantitative reasoning abilities either through undergraduate coursework or standardized test scores, such as GRE quantitative score.

Curriculum Requirements

Total Minimum hours: 31 Credit Hours
•   Shared Core Requirements - 6 Credit Hours
•   Additional required courses -16 Credit hours
•   Electives - 9 Credit Hours

Shared Core Requirements (6 Credit Hours)

Successful completion with a letter grade “B” or better of the two core graduate-level courses is required.

CAI 5005 Introduction to Artificial Intelligence Credit Hours: 3
COP 6536 Advances in Data Structures for IT Credit Hours: 3

Additional Required Courses (16 Credit Hours)

Successful completion with a letter grade “B” or better:

COP 5008 Computing Essentials Credit Hours: 2
COT 5105 Discrete Structures Essentials Credit Hours: 2
COP 5532 Data Structures Essentials Credit Hours: 2
CAI 5035 Mathematics for Artificial Intelligence Credit Hours: 3
COP 5230 Object-Oriented Programming Essentials Credit Hours: 2
COT 5407 Algorithms Essentials Credit Hours: 2
CAI 5026 Ethical Issues in Artificial Intelligence Credit Hours: 3

Electives (9 Credit Hours Minimum)

With prior permission from the Graduate Director, students can take a maximum of 3 hours of Independent Study or Internship, a maximum of three (3) hours of one-hour seminar courses.

Graduate elective courses are separated into two categories: deepening and broadening. Students must select at least 6 hours from the list of deepening electives and at least 3 hours from the list of broadening electives in consultation with the Graduate Director.

Examples of deepening AI courses (6 Credit Hours):

CAI 5135 Data Mining Credit Hours: 3
CAI 5205 Deep Learning Credit Hours: 3
CAI 5307 Natural Language Processing Credit Hours: 3
CAI 5615 Affective Computing Credit Hours: 3
CAI 5815 Autonomous Mobile Robots Credit Hours: 3
CAI 5845 Computer Vision Credit Hours: 3
CAI 5846 Digital Image Processing Credit Hours: 3
CAI 6605 Trustworthy AI Systems Credit Hours: 3
CAP 6100 Human Computer Interface Credit Hours: 3
CAP 6109 Brain-Computer Interfaces Credit Hours: 3
CAP 6455 Advanced Robotic Systems Credit Hours: 3
CAP 6632 Automated Reasoning and Theorem Proving Credit Hours: 3
CAP 6672 Robot Intelligence and Computer Vision Credit Hours: 3
CIS 6900 Independent Study Credit Hours: 1-19
CIS 6930 Special Topics Credit Hours: 1-5
taken as:
- Topics in NLP (3 Credit Hours for this program)
- Social Network Analysis (3 Credit Hours for this program)
- Security & Privacy in ML (3 Credit Hours for this program)
- Hardware Accelerators for ML (3 Credit Hours for this program)
- Augmented Reality (3 Credit Hours for this program)
- Computational Methods for Imaging (3 Credit Hours for this program)
- Smart & Connected Health (3 Credit Hours for this program)
- Seminar in AI Credit Hours: (1 Credit Hour for this program)
CIS 6946 Internships/Practicums/Clinical Practice Credit Hours: 0-3
Or other graduate course approved by the Graduate Director
Examples of broadening AI elective courses (3 Credit Hours):
ISM 7930 Selected Topics in Management Information Systems Credit Hours: 1-3 taken as Fundamentals of AI (3 Credit Hours for this program)
RED 6449 AI Literacy and Technology: Navigating Extended Reality, Interactive Media, Gaming, and Cyberspace Credit Hours: 3
Special Topics Course taken as AI Literacy and Technology, Navigating Extended Reality, Interactive Media, Gaming, and Cyberspace (3 Credit Hours for this Program) (Proposed as RED 5449)
JOU 5367 AI and the Future of Media: Trends, Technologies & Ethics Credit Hours: 3
Or other graduate course approved by the Graduate Director

Comprehensive Exam

Students must pass the comprehensive exam in the semester prior to the semester of graduation.

Exit Survey

All students are required to complete the College exit survey.

University of South Florida

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