Below are answers to some of the most frequently asked questions we've received regarding Binghamton University's Master of Science in Data Analytics graduate degree program.

If you question is not answered here, please reach out to us at msda@binghamton.edu.

Program questions

Admissions questions

  • When is the application deadline?

    We have rolling admissions. However, for the 2022 cohort, preference will be given to those who apply by March 15, 2022. Applications will still be accepted after March 15.

  • Can international students apply for the program?
  • What are the admission requirements of the program?

    Admission requirements can be found here.

  • Do I need to have a STEM degree to be admitted to the program?

    To be considered for admission, applicants must have a strong quantitative background. Students with degrees in mathematics, statistics or other applied sciences (business, economics, political science, engineering, etc.) are likely to have the background.

    Students need to have familiarity with the following broad areas to be successful in the program:

    • Calculus (especially differential calculus used in optimization)
    • Probability (used in understanding data distributions)
    • Statistics (to help in understanding how to analyze and present data and relationships in the data)
    • Computer programming language (helpful in machine learning, data mining, web scraping, etc. Some coding experience and basic knowledge of data structures and algorithms are required.)

    Applications will be evaluated on a case by case basis. Reach out to us at msda@binghamton.edu with questions.

  • Are GRE/GMAT scores required?
    GRE or GMAT scores are accepted, but not required.
  • Can I be admitted for a spring start?
    No - the MS Data Analytics program is highly integrated, with courses taking place in a very particular sequence. Therefore we are only able to admit students for a fall start.


  • What are the guidelines for participating in the 2022 Commencement ceremony?

    While you officially finish your coursework in June 2022, you are still able to participate in Commencement 2022.

    1. Please fill the “Graduate Application for Degree” (GAFD) for Summer 2022 degree conferral in June. The GAFD is available via the "Student" tab in BU Brain. 
    2. Once you successfully fill your Graduate Application for Degree, check your email for a personalized link to the Recommendation for Award form. Fill out this form in your BU portal, and add Manoj Agarwal as your advisor. Once he receives your Award Form, he will check that you have completed all requirements, then certify it. Instructions for the GAFD and Recommendation for Award form can be found at this link
    3. Student Records will then process the actual degree documents which you should receive by August 2022. If you have any questions, please send them to degree@binghamton.edu 

    You will be able to walk in the commencement in May 2022, even though you have not finished all the coursework. You need to follow these guidelines, as described on the Commencement Page:

    • File a commencement Petition by March 23, 2022
    • File the intent to participate by March 23, 2022
    • Request guest tickets by April 29, 2022
    • Request Cap and Gown by March 15, 2022

    The ceremony that MS Data Analytics students will participate in takes place at 4:30 p.m. on Friday, May 20.

  • Can I transfer any credits into the program from an MS program at another university?

    The Graduate School allows up to six credits to be transferred after a student has been admitted and has joined the program. The transfer of credits is subject to approval by the program director.

  • Are financial aids available for students? Do you offer graduate assistantships?

    Please contact the Student Accounts office for details on financial assistance. 

    You can learn more about financial support opportunities for Graduate Students at this link.

    U.S. citizens and permanent residents are encouraged to learn more about our highly competitive Clifford D. Clark Diversity Fellowships. Learn more at this link.

    We do not offer any assistantships.

  • What codes do I use for GMAT/GRE?

    The institution code for Binghamton University is 2535, while the Data Analytics department code is 4323.

  • I'm a Binghamton University undergraduate student. What courses can I take now to help me prepare for this graduate program?

    Students need to have familiarity with the following broad areas

    • Calculus (especially differential calculus used in optimizing)
    • Probability (used in understanding data distributions)
    • Statistics (helping in understanding how to analyze and present data and the relationships in the data)
    • Computer programming language (helpful in machine learning, data mining, web scraping, etc.)

    Calculus courses

    Must have Calculus 1: Differential & Integral Calculus (MATH 224/MATH 225: this is a one semester course) or Business Calculus (MATH 220). Topics include differential calculus covering limits, continuity, and differentiation, integral calculus, optimization and integration.

    Students preferably should also have taken a higher calculus course like Calculus II (MATH 226/227) or Calculus III (Math 323)

    Algebra course

    Needs understanding of matrices and determinants, linear transformations. Linear Algebra (MATH 304) or equivalent. This is not a pre-requisite but would be extremely helpful.

    Statistics courses

    Must have equivalent of MATH 147/148 (topics include data analysis, probability, normal curve, regression, confidence intervals, hypothesis testing)

    Can have other higher level courses - Probability Theory (MATH 447), Mathematical Statistics (MATH 448), or Probability with Statistical Methods (MATH 327) 

    Programming courses

    Knowledge of any of the programming languages like R, Python, C++ will also be extremely helpful.

    A course like CS 110 would be helpful. (An introductory course for students with little or no programming experience. Basic control flow, data types, simple data structures and functions using a scripting language. Developing code using an integrated environment. The basics of directories, files and file types, including text files. Simple examples of the applications enabled by a modern, platform-independent scripting language such as GUIs, event handling, database access and web programming.)

    A new course MATH 247/CS 207 (Introduction to Data Science) is also being taught for the first time in Fall 2019 and will be repeated later. This course provides a broad overview of data science’s different areas, from statistics, machine learning to data engineering and many data science applications. The course teaches critical concepts and skills in computer programming and statistical inference, in conjunction with hands-on analysis of real-world data sets, including economic data, document collections, geographical data, and social networks. This course is designed to provide a non-technical introduction to the data science approach. It is intended both for students from non-quantitative fields and those from a quantitative field who are interested in data science. The prerequisite for this course includes working knowledge in high school math (MATH 108 or equivalent), a course in introductory statistics (at the level of MATH 147, MATH 148 or AP statistics with grade 3+, or equivalent).

  • What other data science resources are there at Binghamton University?
  • What resources are available to help students academically?