Frequently Asked Questions

Before Applying

  • What is the total duration of the program?

    For students studying full time (3 classes per term), their degree requirements can be met in 1.5 to 2 years. For students studying part-time (1-2 class per term), their degree requirements cane be met in 3 years.

    Per University Graduate policy, domestic students have a maximum of 5 years to complete our programs. International students will need to speak with the Office of International Services as this is dependent on visa requirements.

  • What are the minimum GRE and TOEFL scores required for entrance into the program?

    Competitive applicants should have a total GRE minimum score requirement of 329; a minimum Quantitative - 165, Verbal - 160, and Analytical Writing - 4.0.

    Competitive applicants should have minimum TOEFL score of 100 on the Internet-based test.

  • Can I apply for admission if I am still in my last year of undergraduate study?

    Yes! You can apply as long as your current degree program is completed before you begin coursework in the Data Science program. During the application stage, submit the most updated version of your transcript.

  • Is the program STEM eligible?

    As the Data Science program is an interdisciplinary and applied program, it is STEM eligible via the U.S Department of Education.

    International students applying for Optional Practical Training (OPT) after graduation may be eligible for a STEM extension. For more information, please speak to an International Advisor at the Office of International Services at ois@iu.edu.

Application Process

  • Who do I speak to if I received an error while trying to submit my online application?

    Our office does not orchestrate the application portal. You will need to contact the University Graduate School whom administers the site for payment.

    Look here for international applicants who are unable to pay through PayPal. You may also email ois@iu.edu, which is the Office of International Services for assistance.

  • How long does the admission and review process take?

    The application portal for the Data Science programs typically open on September 1st of every year. The Data Science program operates on an admissions deadline system, not rolling admissions. The deadlines vary depending on the program to which you are applying.

    The Data Science Graduate Office begins processing applications for the Residential MS applications by mid-September and the Online MS and Certificate applications by mid-February.

    The length and time for the review process will vary depending on time of year, the number of applications, and the size of the Admissions Committee. Once an application is complete and forwarded for review, the committee strives to complete the review process in about 4-5 weeks from the application deadline.

After Admissions

  • Can I transfer some courses to count towards the program?

    That depends! We do not permit any credits to be transferred for our Online Certificate program, since it requires only 4 courses (12 credit hours).

    For our Online MS or Residential MS program, a maximum of 9 credit hours of graduate course work with grades of B (3.0) or higher may be transferred from other accredited colleges and universities. Please note these credits cannot have counted towards another program where a degree or professional certificate was conferred.

    Courses such as Data Mining, Statistics, Machine Learning, and Algorithms are generally approved for transfer.

  • Do online students have an opportunity to participate on-campus?

    We host several on-campus activities each year and online students are welcome to join us at any of these events.

    To enhance the online learning experience, the Data Science Graduate program hosts optional Online Immersion Weekends (OIW) specifically for our online students. These weekends are held on the Indiana University Bloomington campus in the Spring terms – typically for 3 days (Thursday – Saturday).

    During the Immersion Weekends, students will participate in face-to-face presentations by faculty and other national experts, receive hands-on experience with new data sets, and network with other students, faculty and administrators. This is not mandatory but it is a great experience and many students enjoyed themselves!