A High-Demand Field With Growth Opportunities
Launch your career in artificial intelligence and data science through a cutting-edge curriculum designed for the next generation of intelligent systems and data-driven innovation. The M.S. in Artificial Intelligence and Data Science provides advanced training in AI, machine learning, generative AI, large language models (LLMs), data engineering, cloud computing, MLOps, and intelligent analytics.
Through hands-on projects, applied research, and industry-informed coursework, students develop the technical and analytical skills needed to build scalable AI-driven solutions and prepare for high-demand careers across rapidly growing industries.
Advance your career in Artificial Intelligence and Data Science. Apply now.
- Degree Type
- MS
- Area of Interest
- Computing & Technology
- Associated Colleges or Schools
- Program Location
- Queens Campus
- Required Credit Hours
- 30
Contact Us
We are here to answer your questions about the program and admission process.
Please contact:
Justin Goldberg
Graduate Assistant Dean
[email protected]
Program Director
Dr. Fazel Keshktar
Recognized Excellence
ABET Accrediated
The M.S. Artificial Intelligence and Data Science program is accredited by the Computing Accreditation Commission of ABET, under the commission’s General Criteria, with no applicable program criteria.
Program at a Glance
Focused curriculum in Artificial Intelligence and Data Science, including machine learning, deep learning, generative AI and large language models (LLMs), data engineering, cloud computing and MLOps, intelligent analytics, and applied AI systems development.
Degree Credits Required
Months (full-time)
Estimated Time To Complete
Evening Courses Available
Program Information
The M.S. Artificial Intelligence and Data Science program requires 30 credits that include the following:
Core Courses
15 credits
- CUS 720 — Software Design & Architecture for AI Systems
- CUS 730 — Cloud Computing & MLOps
- CUS 740 — Generative AI & Large-Language Models
- CUS 752 — AI & Machine Learning Foundations
- CUS 756 — Deep Learning Models in Machine Learning & Generative AI
Analytical Foundation Electives
6 credits selected from the following courses
- BUA 602 — Business Analytics
- BUA 609 — Advanced Managerial Statistics
- BUA 633 — Predictive Analytics and Business Forecasting Models
- BUA 610 — Data Visualization Applications
Technical Applied Electives
6 credits selected from the following courses
- CUS 510 — Database Management Systems
- CUS 620 — Intro Programming for Analytics
- CUS 625 — Data Visualization Programming
- CUS 680 — Big-Data Analytics
- CUS 716 — Algor. & Theory for Intelligent Systems
- CUS 725 — Databases for AI & Data Engineering
- CUS 754 — Computer Vision and Applications
- CUS 758 — Responsible AI & GenAI Security
- CUS 795 — Thesis I
- CUS 900 — Internship
- CYB Elective
Capstone/Thesis
3 credits selected from the following courses
- CUS 790 — Master’s Capstone Project
- CUS 796 —Thesis II (Pre-requisite: CUS 795)
The program is designed to prepare graduates to become impactful professionals in artificial intelligence and data science within a few years of graduation.
- Develop, deploy, and evaluate artificial intelligence and data-driven solutions in industry, research, or advanced computing environments.
- Apply artificial intelligence, machine learning, data science, and intelligent systems methodologies to solve complex problems across diverse application domains.
- Engage in continuous learning and professional development to remain current with emerging advances in artificial intelligence, data science, computing technologies, and ethical AI practices.
- Contribute to the advancement of artificial intelligence and data science as innovators, researchers, technical leaders, or entrepreneurs.
Graduates of the program will have the ability to:
- Analyze complex computing and data-driven problems and apply principles of artificial intelligence, data science, machine learning, and computing to develop appropriate solutions.
- Design, implement, evaluate, and deploy AI- and data-driven systems that meet specified technical, functional, and user requirements.
- Communicate effectively in a variety of professional, technical, and interdisciplinary contexts.
- Recognize professional, ethical, legal, and societal responsibilities related to artificial intelligence, data science, and computing practice, and make informed judgments accordingly.
- Function effectively as a member or leader of multidisciplinary teams engaged in the development, evaluation, and deployment of AI and data science solutions.
Admission Requirements
All applicants must possess a bachelor’s degree from an accredited institution or the international equivalent before enrollment at the graduate level. In addition to the application form and non-refundable application fee, candidates should submit the following:
- Statement of professional goals and resume, which can be uploaded as part of the application for admission.
- Official transcripts from all undergraduate, graduate, and professional schools attended.
- One letter of recommendation obtained from a professional or academic reference.
- Sufficient previous coursework in calculus/statistics or equivalent mathematics courses.
- Official TOEFL, IELTS, PTE or Duolingo scores are required for applicants whose native language is not English.
- Students with international credits must submit a course-by-course foreign credit evaluation with GPA calculation from a NACES member.
For additional information, please contact:
Office of Graduate Admission
[email protected]
718-990-1601
Shiqi Chen ’18MS
“Transitioning from a medical background to the field of data science was a significant turning point in my career. The inclusive and diverse environment at St. John’s University provided me with the opportunity to pursue my passion for data science, despite coming from a nontraditional background. Since completing the M.S. program, I have witnessed significant growth in my career as a data scientist.”
Peter Tadrous ’20CCPS, ’21GCCPS
“The Data Science program at St. John’s has been instrumental in equipping me with robust skills in statistics, data wrangling, and data visualizations. The program inspired me to see the malleability of data and how I can shape it into meaningful insights. The educators at St. John’s have fueled my curiosity and propelled a continual journey of discovery in data science.”
Brad Rose ’20MS
“I was thankfully able to use my military benefits to continue my higher education at St. John’s, which led to employment in the fintech industry at J.P.Morgan. I did so late in life; it’s never too late to get an education. For those of you who are getting one early, remember how fortunate you are to have the support structure and ability to do so.”
Potential Career Opportunities
- AI Engineer
- AI Product Specialist
- AI Research Associate
- AI Solutions Architect
- AI Software Developer
- Applied AI Scientist
- Business Intelligence Analyst
- Cloud AI Engineer
- Computer Vision Engineer
- Data Analyst
- Data Engineer
- Data Scientist
- Generative AI Engineer
- Intelligent Systems Developer
- Large Language Model (LLM) Engineer
- Machine Learning Engineer
- MLOps Engineer
- NLP Engineer
- Predictive Analytics Specialist
- Responsible AI and AI Governance Specialist
The Institute for Artificial Intelligence and Data Science
The Institute for Artificial Intelligence and Data Science at St. John’s University serves as a center for interdisciplinary research and innovation in artificial intelligence, machine learning, data science, and analytics. Researchers collaborate across the Collins College of Professional Studies and the broader University to advance AI-enabled discovery, responsible innovation, and data-driven decision making.
AI Evolution: What is a Large Language Model?
Many people use Artificial Intelligence (AI) chatbots like ChatGPT and Gemini. They give you the answers you want without doing an extensive deep dive through a Google search. But have you ever wondered what a large language model is and how it can generate such excellent responses?
AI Opportunities
Break Through Tech AI Program (Cornell University)
Break Through Tech, an initiative of Cornell University, offers a free, virtual, one-year extracurricular AI program for students interested in artificial intelligence, machine learning, and data science. Participants build foundational skills over the summer, work on real industry projects during the academic year, and gain hands-on experience with industry-standard tools—along with mentorship, career coaching, and internship support.
Applications are now open for the 2026–2027 academic year and close on February 16, 2026. Participants earn a Machine Learning certificate from Cornell University and receive a financial award upon completing the program.
Click here to apply.
AI4ALL IGNITE
AI4ALL Ignite is a career accelerator program offered at no cost to students, equipping you with in-demand, hands-on technical skills for AI internships and early career roles. You'll gain industry connections, industry-specific career readiness guidance, a certificate of completion, and a responsible, human-centered approach to AI.
Click here to apply.
AWS (Amazon Web Services) Academy Member Institution
M.S. Data Science students have obtained AWS Cloud Foundation certification through the distributed big data courses.
Databricks University Alliance Member
IBM AI Alliance Member
Meet Our Faculty
Interested in Computing & Technology , but not sure if Artificial Intelligence and Data Science, Master of Science (M.S.) is right for you?
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