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 your question is not answered here, please reach out to us at msda@binghamton.edu.
What financial information do students need to know?
Full time MSDA students take 12 credits per semester (fall and spring) and 3 credits in winter and summer, totaling 30 credits per year. Students are billed separately for each semester.
What do students need to know about scholarships?
U.S. citizens and permanent residents are encouraged to learn more about our highly competitive Clifford D. Clark Diversity Fellowships. You must complete your application to the MS Data Analytics program by Jan. 15 to apply for this fellowship.
We do not offer any assistantships.
What to know about our program
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I'm not in the Master of Science in Data Analytics program. Can I still take DATA
classes?
Only students in the MS Data Analytics program are eligible to take the graduate-level DATA courses.
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How long does it take to complete the Master of Science in Data Analytics program?
Students are expected to complete the program in about 10 months. Classes begin in the fall and end after summer term I.
You can view Binghamton University's academic calendar here.
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What does the program curriculum look like?
You can find the program curriculum and course information here.
- Do you offer this program to part-time students?
Yes, we offer a course sequence to part-time students that can be completed in two years. Learn more about our part-time option on our Curriculum page.
Because the program is held in-person on the Binghamton campus, part-time students are required to attend in-person. Please note that most MS Data Analytics courses take place during the daytime, so students will need to have permission from their employer to allow time-off for courses and course-related activities such as group meetings.
- Is this program available online?
No, this program is not currently available online. However, we anticipate making it available online in the future. Please stay in touch with us for updates on progress.
What to know about Admissions
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When is the application deadline?
We have rolling admissions. However, preference will be given to those who apply by March 15. Applications will still be accepted after March 15, but seats are not guaranteed.
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Can international students apply for the program?
Yes, international students can apply. See more information here or reach out to us at msda@binghamton.edu.
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What are the admission requirements of the program?
Admission requirements can be found here.
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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:
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Calculus (especially differential calculus used in optimization)
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Probability (used in understanding data distributions)
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Statistics (to help in understanding how to analyze and present data and relationships in the data)
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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.
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Are GRE/GMAT scores required?
GRE or GMAT scores are accepted, but not required.
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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.
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I have a three-year bachelor's degree from India. Can I apply?
We follow the guidelines established by WES. We can accept the three-year as equivalent to a U.S. Bachelor’s degree when the following conditions are met:
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The degree-awarding institution must be a Tier 1 (1st Tier) school, accredited by India’s National Assessment and Accreditation Council (NAAC) with a grade of “A” or better**, and
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The applicant must have graduated in the 1st Class
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The applicant must have graduated in the 1st Class Binghamton University graduate programs could additionally request a WES or equivalent evaluation The applicant must have graduated in the 1st Class
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Student has earned at minimum 126 (equivalent to a Bachelor’s degree) credits.
If you already have a WES evaluation, or equivalent evaluation, we recommend submitting it to your application and sharing it with your academic department.
If you do not have either, WES’ free evaluation tool can be found at this link.
**Please note: This equivalency applies only to institutions accredited by the NAAC. It takes into consideration the relative standing of a university as reflected by the NAAC grade, and the individual degree holder’s performance as indicated by the degree classification of the degree.
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Important student information
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When can I apply for the OPT?
From the International Student and Scholar Services office.
MSDA students graduate in the summer semester (August graduation date). You can apply for OPT up to three months before you graduate. You will be able to apply for your OPT I-20 in May. You can pick an OPT start date between the day after you graduate, up to 60 days after you graduate (which would be sometime in October). More information will be available once the summer 2024 graduation date is scheduled.
Your other option would be to apply for OPT as a course complete student. This would allow you to pick an OPT start date before you graduate in August. For your program, you would be considered course complete after you complete your course in the summer 1 semester (which typically ends in June or first week of July). You would be able to pick a start date as early as July. We only recommend students apply for OPT as a course complete student if they have a solid job offer.
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What are the guidelines for participating in the 2024 Commencement ceremony?
While you officially finish your coursework in June 2024, you are still able to participate in the 2024 Commencement ceremony.
- When you enroll in your Summer 1 course in June, fill the “Graduate Application for Degree” (GAFD) for degree conferral. The GAFD is available via the "Student" tab in BU Brain.
- 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.
- Student Records will then process the actual degree documents which you should receive by August 2024. If you have any questions, please send them to degree@binghamton.edu
You will be able to walk in the Commencement in May 2024, 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 15, 2024
- After receiving confirmation that your petition has been approved, file the Intent to Participate form by March 15, 2024 (available at the top of my.Binghamton.edu)
- Request guest tickets by Feb. 24, 2024
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Request guest tickets in mid March 2024 when they become available
The ceremony that MS Data Analytics students will participate in takes place at 4:30 p.m. Friday, May 10
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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.
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What codes do I use for GMAT/GRE?
The institution code for Binghamton University is 2535, while the Data Analytics department code is 4323.
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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 optimization)
- 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. The topics are also covered in AP Calculus.
Students preferably should also have taken a higher calculus course like Calculus II (MATH 226/227) or Calculus III (Math 323)
Linear 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 both in statistics and in machine learning.
Statistics courses
Must have equivalent of MATH 147/148 (topics include data analysis, probability, normal curve, regression, confidence intervals, hypothesis testing). Similar statistical courses or quantitative research methods courses from the anthropology, psychology, economics, engineering, or management are also acceptable, such as ANTH 200, PSYC 243, ECON 366, ISE 261, CQS 112, and HARP 130 (Intro to Statistical Thinking).
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.
As a minimum, an introductory 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.)
Similar to CS 110 are the HARP 150 and 151 series: HARP 150: Intro to Coding (Python) or HARP 151: Programming in Action, which provides programming skills and lays the basis for computational thinking to liberal arts students. There are no prerequisites for HARP 150. It should be taken in the first or second year. HARP 151 requires HARP 150 as a prerequisite, except for students who have programming experience or have already taken relevant coursework.
Other Python/R courses include:
- GEOG 380R: Spatial Fundamentals in R
- ECON 416: Economic Analysis with Python
- MATH 329: Intro to Scientific Computing
- MATH 488P: Principles of Data Science
- HARP 210: Digital Text Analysis
- PLSC 380H: Visualizing Violence with R
- PLSC 380J: Analyzing Politics Using R
- PLSC 380T: Computational Text Analysis with Python
Binghamton students can consider completing the Digital & Data Studies minor to enhance their data skills.
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What other data science resources are there at Binghamton University?
Binghamton University’s Transdisciplinary Area of Excellence (TAE) in Data Science provides a collaborative environment to produce innovative research, and our library offers a robust collection of resources for the data analytics program.
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What resources are available to help students academically?
Binghamton University student resources Include:
- University Tutorial Services
- The Writing Center
- The Speaking Center
- Students can raise a flag in Starfish to indicate they are struggling, and an appropriate office will follow up with them.
- Our website for students on how to use technology successfully, communicate well in an online environment and manage time and stay motivated when taking classes online.