Hofstra University offers a Master of Science in Data Science through the Department of Computer Science in the Fred DeMatteis School of Engineering and Applied Science.
The 30-credit program is based on the Hempstead campus on Long Island. Machine Learning is a required course, taken alongside required courses in data science, data warehousing, matrix algebra, and statistical inference. Deep learning, data mining, and natural language processing are electives, and students finish with a capstone project or a thesis.
Last reviewed: October 2026
Quick Facts
| Degree | MS in Data Science |
| School | Department of Computer Science, Fred DeMatteis School of Engineering and Applied Science |
| Location | Hempstead, New York |
| Format | Campus, full time or part time |
| Credits | 30 |
| Culminating Experience | Capstone project (3 credits) or thesis (6 credits) |
| Minimum GPA | 3.0 |
| GRE | Optional |
| Application Deadline | Rolling admission for fall and spring |
| Tuition | $1,826 per credit hour for 2026–27 |
Official MS in Data Science page
Curriculum
Hofstra does not offer a standalone master’s degree in machine learning or artificial intelligence. The MS in Data Science is the graduate degree in which Machine Learning is required of every student. It is taught by computer science and mathematics faculty, and half of its required courses are mathematics courses.
Students complete 30 semester hours consisting of:
- 18 credits of required courses
- 6 or 9 credits of electives
- a 6-credit thesis or a 3-credit capstone project
Students need a 3.0 grade point average and a grade of C or better in every course.
Required Courses
- CSC 221 – Data Science
- CSC 222 – Data Warehousing
- CSC 272 – Machine Learning
- MATH 215 – Computational Matrix Algebra and Applications
- MATH 245 – Probability and Statistical Inference
Students also choose one of these mathematics courses:
- MATH 216 – Nonlinear Optimization
- MATH 228 – Combinatorial Optimization
- MATH 246 – Regression Methods of Data Analysis
The Machine Learning course covers regression, neural networks, decision trees, support vector machines, ensemble methods, clustering, and graphical models.
Electives
Students on the thesis route take two electives and students on the project route take three, chosen under advisement from:
- CSC 220 – Neural Networks and Deep Learning
- CSC 249 – Text Mining
- CSC 254 – Database Design
- CSC 259 – Concurrent and Parallel Programming
- CSC 273 – Data Mining
- CSC 274 – Natural Language Processing
- CSC 284 – Computer Communication Networks and Distributed Processing
- MATH 228 – Combinatorial Optimization
- MATH 246 – Regression Methods of Data Analysis
Other courses can be taken with prior approval from the graduate program director. Neural Networks and Deep Learning, Data Mining, and Natural Language Processing are electives rather than required courses, and the plan has room for only two or three electives in total.
Capstone Project or Thesis
The capstone project lasts one semester and applies data science techniques to a problem. Students complete CSC 300 – Independent Projects or CSC 303 – Graduate Capstone Project and submit a report and a presentation.
The thesis is intended for students interested in research and lasts two semesters. Students complete CSC 301 – Thesis Background Research and CSC 302 – Thesis. Either route requires a proposal approved by the advisor and the graduate director.
Related Option: MS in Computer Science
Hofstra’s 30-credit MS in Computer Science has an optional Artificial Intelligence concentration. It requires CSC 270 – Artificial Intelligence and CSC 272 – Machine Learning, plus one course from Text Mining, Data Mining, Natural Language Processing, or CSC 279 – Computer Vision. That degree also requires core courses in algorithms, programming languages, and operating systems.
Cost and Tuition
Hofstra is a private university and charges graduate tuition by the credit hour, with the same rate for New York residents and nonresidents.
For the 2026–27 academic year, the university lists:
| Category | Amount |
|---|---|
| Graduate tuition, per credit hour | $1,826 |
| University Fee, per term (8 to 11.99 credits) | $225 |
| Technology Fee, per term (8 to 11.99 credits) | $65 |
| Activity Fee, full-time graduate students | $30 |
At 30 credits, tuition comes to about $54,780 before fees and scholarships. The University Fee and Technology Fee are $392 and $115 per term for students taking 12 or more credits, and $115 and $40 for students taking fewer than 8.
All graduate applications are reviewed for merit-based scholarships by the program director, with no additional materials required. Rates can change each year, so students should confirm current costs with Student Financial Services.
View Hofstra University tuition and fees
Admission Requirements
Applicants need a bachelor’s degree in mathematics, computer science, or a related discipline from an accredited institution.
The program requires a minimum 3.0 GPA.
Applicants are expected to have completed, with a grade of B or better:
- programming principles and techniques, with coursework or substantive work experience in Python and R
- algorithms and data structures
- Calculus I and Calculus II
- linear algebra
Applicants who meet every criterion except the prerequisites may be admitted as provisionally matriculated students. They must satisfy the prerequisites before completing 12 semester hours of graduate study, through coursework or a proficiency examination.
Application Materials
Applicants submit:
- online graduate application and $75 application fee
- transcripts from each institution attended
- proof of English proficiency when required
Submission of GRE or GMAT scores is optional. Unofficial transcripts can be uploaded for review, and official transcripts are required after acceptance. Applicants who submit a statement of purpose are encouraged to describe their commitment to data science and their goals.
International applicants can show English proficiency with a TOEFL score of 80, an IELTS score of 6.5, or a Duolingo score of 120, among other options.
Application Deadlines
Hofstra does not publish a fixed application deadline for this program. Applications are reviewed on a rolling basis for fall and spring entry, and students may request to begin in a summer session.
The admissions committee prefers that students apply at least two weeks before classes begin. International applicants should allow additional time for the tuition deposit, financial documents, and Form I-20.
Program Format
Classes meet on the Hempstead campus, Monday through Friday, in the fall, spring, and summer sessions and sometimes in the January session. In-person classes usually have no more than 22 students.
Hofstra describes the program as having flexible learning formats but does not state that the degree can be completed online. Students who need online study should confirm course availability with the graduate program director.
Students can enroll full time or part time. Hofstra states that the program can be finished in one academic year full time or two academic years part time, and defines full-time study as nine semester hours in the fall and spring.
Students can apply for paid positions with employers through the DeMatteis Co-op Program. Prospective students can also take up to 12 credits as nonmatriculated students before applying.
Who Is This Program Best For?
Hofstra’s MS in Data Science is a good fit for students with a mathematics or computing background who want required machine learning and its mathematical foundations in a small campus program on Long Island.
It may be especially appealing to students interested in:
- machine learning with required coursework in linear algebra, statistical inference, and optimization
- data science and data warehousing
- electives in deep learning, data mining, text mining, and natural language processing
- a choice between a research thesis and a one-semester capstone project
- rolling admission with optional GRE scores
- paid co-op experience during the degree
The program is a data science degree with one required machine learning course. Deep learning and natural language processing are electives, the plan has room for only two or three electives, and there is no artificial intelligence or computer vision course in its own course list. Tuition is charged at a private university rate, and Hofstra does not state that the degree can be completed online. Students who want a degree built entirely around AI, a fully online program, or public university pricing may want to compare other New York schools.
Official Hofstra University Program Links
- MS in Data Science program page
- MS in Data Science requirements
- About the program and frequently asked questions
- Graduate Studies Bulletin entry
- Graduate application page
- International graduate admission
- Tuition and fees
Related Machine Learning Programs in New York
Students can also compare Hofstra University with other master’s programs in machine learning, artificial intelligence, and related fields offered in New York.
- Binghamton University – Binghamton
- City College of New York – New York
- Clarkson University – Potsdam
- Columbia University – New York
- Cornell University – Ithaca
- Fordham University – New York
- Long Island University – Brooklyn
- Manhattanville University – Purchase
- Marist University – Poughkeepsie
- Mercy University – Dobbs Ferry
- New York University – New York
- Pace University – New York
- Rensselaer Polytechnic Institute – Troy
- Rochester Institute of Technology – Rochester
- St. John’s University – Queens
- Stony Brook University – Stony Brook
- SUNY Buffalo State University – Buffalo
- SUNY New Paltz – New Paltz
- SUNY Oswego – Syracuse
- SUNY Polytechnic Institute – Utica
- Syracuse University – Syracuse
- University at Albany – Albany
- University at Buffalo – Buffalo
- University of Rochester – Rochester
- Utica University – Utica
- Yeshiva University – New York