Please see below for information about applying to the Data Science Master's Program. Admission is rolling, with a final deadline of February 1. We do not guarantee an early response for early applications.
Deadline: February 1
Applications open in early September for the following fall. All students begin the program in the fall (September); there is no option to start in spring. Admission is rolling, which means we may accept some students before the February 1 deadline. No applications can be accepted after February 1. You will be notified by the Graduate School if you are admitted. We expect to contact admitted and waitlisted applicants by the end of February.
Please provide unofficial (scanned) copies of your transcripts as part of the electronic application. You will be prompted to mail an official copy of your transcript if you accept an offer of admission.
- GRE: Not required
- Record of grades or other academic performance; we do not require WES or other external evaluation of international transcripts
- CV or resume
- Personal statement (experience, interests, plans for the future; what should we know about you?)
- Writing sample (optional): If you have written a technical article or paper which you feel would help us evaluate your preparation for the program, this is where you would attach it.
- Letters of recommendations (3 minimum, 5 maximum; suggest to your letter writers that they look at this site)
- TOEFL (for applicants whose native language is not English; see testing and waiver policies here)
- Reporting code for tests: 3094 (no departmental code)
We seek to admit students from a wide range of backgrounds for distinctive careers in Data Science. This means that students will have a wide range of experience through work and education, which can prepare them for the program in a variety of ways. There are no fixed prerequisites for the program, however you will need a certain level of math, statistics, and computing experience in order to succeed.
At a minimum, we recommend that students entering the program have completed at least a year of calculus (at the level of MATH 0090 & 0100), a semester of linear algebra (at the level of MATH 0520), a semester of calculus-based probability and statistics (at the level of APMA 1650), and an introduction to programming (at the level of CSCI 0150 or 0170).
We also admit exceptional students who lack one or more of the minimum requirements in linear algebra, probability and statistics, and computer science. These students will be expected to take a course at Brown or elsewhere to achieve the necessary preparation before the program begins, and should consult with the program director to determine what is most appropriate.
If you have questions about your preparation for this program, please carefully read the course descriptions linked above. You can also take a look at our online program preparation modules: if you are not familiar with the material taught in those modules, you will need additional preparation. You can use those modules or other online courses to get the needed preparation.
You do not have to complete your preparation for the program before you apply!
We consider numerous criteria including academic performance, letters of recommendation and industry experience. We also consider GRE scores, TOEFL/IELTS scores (if relevant), motivation, work experience, awards, honors, prizes, and other accomplishments. Because master's applicants are so diverse, no single set of criteria adequately cover all the cases.
Please note: There are no eligibility criteria for application, such as minimum GPA or GRE scores (but see recommended minimums for English-language test scores).
Factors we consider when evaluating applications include:
- Academic performance: The GPA is not the only criterion. The grades in data-science related areas are also important. Also, we take into account the fact that at some very competitive schools it is very difficult to achieve a high GPA.
- Letters of recommendation: Letters must give a detailed, factual, and candid evaluation of the applicant's capabilities. Rankings and comparisons with other students are very useful. Ask your recommender to follow these guidelines. Remind your recommenders of deadlines to ensure they are met.
- Personal Statement: The statement that accompanies your application is an important element that helps us learn more about you. There is no required length or topic, but we would like to learn more about your background and expected future in data science at a minimum.
- Work experience: Please describe any work experience you might have. Not all applicants have work experience, but for those who do, some description of it helps us better evaluate your application.
- GRE scores: These scores let us compare the basic skills of applicants from diverse backgrounds. We are aware that (1) test performance can improve considerably with practice, (2) some people do not perform well on tests, (3) and the verbal GRE is harder for some foreign applicants. The GRE is not required for the 2021 application cycle.
- TOEFL and IELTS scores: Applicants whose native language is not English and who have not received a college degree from an institution where the instruction is in English must take the TOEFL or IELTS exam. Additional evidence (e.g., certificate of completion of an English course) may also be submitted. We generally do not consider applicants who have scored below 620 (PBT) or 260 (CBT) or IBT (105), and prefer scores higher than that. The corresponding minimum IELTS score is 7.5. If you are exempt from taking the an English language test, please email the Graduate School directly at [email protected] to get a waiver. More information.
- Awards, honors, and prizes: Unless they are well-known (e.g., NSF fellowship or graduation with honors), please give details about them (how many candidates? how many awards? what were the selection criteria?). This is especially important for foreign applicants. If these awards are really important, we would expect your recommenders to mention them.
- Research experience: Research experience is not required for master's applicants and many of our applicants do not have any, but you can use experience you've had to demonstrate your ability to handle graduate-level data science material.
The Data Science Initiative (specifically, a group of faculty members) evaluates your application and makes recommendations to the Graduate School, which typically follows our recommendations. Therefore, you are generating your application (in particular, your statement) to be read primarily by the faculty of the Data Science Initiative. You will be notified by the Graduate School if you are admitted.
The annual tuition for the DSI Master's Program for 2020–2021 is $69,204. Tuition and fee information is listed on the Bursar's website.
Because the program comprises 4 fall credits, 4 spring credits, and 1 summer credit, the total cost of the program is equal to the annual tuition plus one-eighth of the following year's annual tuition (since summer courses fall in the following fiscal year). Based on an expected tuition increase of 5%, the full cost for completing the program in 12 months will be the annual tuition of $69,204 + (one summer credit) $9,083 = $78,287.
(Important note: students choosing to take longer than 12 months to complete the program will pay tuition for the semester in which they take credits: a class taken in fall of 2021 will be charged at the 2021-2022 tuition rate, no matter when the student started the program.)
We do not currently have scholarships available for this program. Brown's Office of Financial Aid can help with loan funding; you can find information and a financial worksheet here.