Students and faculty looking at projected data models

Data Science, M.S.

The graduate program leading to a Master of Science in Data Science is designed specifically for all students or working professionals who wish to pursue a career in Data Science (data analytics, machine learning, big data management, data visualization, etc.). The program is capable of serving a wide range of professional interests, and within this framework takes a practical approach to computer applications. Students can complete the degree program either with traditional in-person classes or with flexible online courses.

Program Overview

New York Institute of Technology’s program is open to students from diverse professional backgrounds who have a baccalaureate degree in computer science, engineering, management, information technology, mathematics, or a related field of interest.

Specific objectives of this program are to provide students with a comprehensive background in:

  1. Fundamental areas of data science such as algorithms, computational theory, analytics, operating systems, compiler design, and machine learning.
  2. Theory and design of modern high-level programming languages and applications in development of data systems.
  3. Design and analysis of efficient algorithms.
  4. Advanced topics in computer architecture, illustrated by case studies from classic and modern processors including large-scale computer systems.

The curriculum consists of 30 credits, 15 of which are allocated to required courses in data science. The remaining 15 credits permit students to specialize either in areas appropriate to their individual needs, or to complete the thesis option. In order to accommodate working professionals, courses are offered during day and evening hours, as well as weekends at the Long Island and New York City campuses.

Our emphasis on real-world, applications-oriented training is ideal for individuals interested in Data Science (data analytics, machine learning, big data, data visualization, etc.). Graduates of the program will also have the opportunity to receive specialized training in commercialization and entrepreneurship via the Entrepreneurship and Technology Innovation Center (ETIC).

Thesis Option Master’s Degree
Students selecting this option will be required to complete 30 credits, including six credits of M.S. thesis courses and nine credits of general electives. Full-time students typically take two semesters to complete the thesis course sequence, which entails planning and conducting research and writing a thesis. Depending on the thesis topic, students will gain specialized skills and knowledge to make them better qualified for research and development jobs at companies. The thesis may also lead to advanced degrees beyond the Master of Science. With the approval of a supervising thesis advisor, qualified students pursuing the master’s thesis must:

  • Enroll in two semesters of DTSC 890 MS Thesis I and DTSC 891 MS Thesis II for a maximum of six credits.
  • Prepare reports and verbally defend a formal thesis in accordance with criteria established by the College of Engineering and Computing Sciences. A formal written thesis will be archived in the university library.

Note: All master’s thesis students must strictly adhere to the Master’s Thesis Policies and Guidelines published by NYIT College of Engineering and Computing Sciences.

Non-Thesis Option Master’s Degree
Students selecting this option will still be required to complete 30 credits total, but instead of M.S. thesis courses, students will take twelve elective credits and a three-credit project course (DTSC 870).

Fellowships and Assistantships
Research fellowships and teaching assistantships are available to qualified candidates. These opportunities are usually for a 10-month period and may include partial remission of tuition and fees.

International F-1 students who successfully complete this degree are eligible for an additional 24-month STEM OPT extension to work in the U.S. in an area directly related to their area of study immediately upon completing the customary 12-month post-completion Optional Practical Training (OPT).

To apply for the M.S. in Data Science, visit

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Admission Requirements

  • Applicants must possess a bachelor's degree from an accredited institution, with a GPA of 2.85 or higher on a 4.0 scale.
    • Applicants who do not qualify for full matriculation and have an undergraduate GPA between 2.5 and 2.84 may be conditionally admitted at the discretion of the program director.
  • As data science is an interdisciplinary field, we welcome applicants from diverse professional backgrounds. However, applicants should have the following prerequisites:

    1. One computer programming course
    2. One college-level statistics course
    3. Basic linear algebra
    4. Basic database systems
  • Students with an insufficient background for direct admission into the Data Science M.S. program may be admitted if they take the required prerequisite course(s), with the approval of the program director.
  • Submit GRE scores

    • Graduates of foreign universities are required to take the GRE and submit their scores.
    • U.S. students with a GPA below 2.85 may, at the discretion of the dean, be asked to take the GRE or other diagnostic tests. Admission will be based upon consideration of test results, previous academic performance, and related employment, if applicable.

Application Materials

  • Completed application
  • $50 nonrefundable application fee
  • Copies of undergraduate transcripts for all schools attended. All final, official transcripts must be received prior to the start of your first semester.
  • Copy of college diploma or proof of degree
  • Official GRE scores, if required (GRE Code: 2561)
  • International student requirements: English proficiency (TOEFL/IELTS/PTE), I-20, and transcript evaluation

Transfer Credits

  • Students may transfer up to nine credits from an accredited graduate program for appropriate courses in which a minimum grade of B was earned.
  • Pass grades earned during the spring 2020 semester meet this GPA threshold and are transferable to New York Institute of Technology.