Master of Science in Data Science
The Data Science Initiative at Brown offers a new master's program (ScM) that will prepare students from a wide range of disciplinary backgrounds for distinctive careers in Data Science. Rooted in a research collaboration among four very strong academic departments (Applied Mathematics, Biostatistics, Computer Science, and Mathematics), the master's program will offer a rigorous, distinctive, and attractive education for people building careers in Data Science and/or in Big Data Management. The program's main goal is to provide a fundamental understanding of the methods and algorithms of Data Science. Such an understanding will be achieved through a study of relevant topics in mathematics, statistics and computer science, including machine learning, data mining, security and privacy, visualization, and data management. The program will also provide experience in important, frontline data-science problems in a variety of fields, and introduce students to ethical and societal considerations surrounding data science and its applications.
The program's course structure, including the capstone experience, will ensure that the students meet the goals of acquiring and integrating foundational knowledge for data science, applying this understanding in relation to specific problems, and appreciating the broader ramifications of data-driven approaches to human activity. Moreover, our strong industry partnerships will help you better learn about industry's needs and directions, and will expose you to novel and unique opportunities. In addition, several professors from all across the different department's groups work closely with industry (regional and beyond) and the government, so you will be able to sharpen your skills here on problems that bring research ideas and methods to bear on problems of practical value.
The program will be conducted over one academic year plus one summer, with the option for an additional pre-program summer for students who lack one or more of the basic prerequisites. The regular program includes two semesters of coursework and a one-summer (5- 10 week) capstone project focused on data analysis in a particular application area.
There are nine credits unites required to pass the program: four in each of the academic year semesters, and one (the capstone experience) in the summer. The nine credit-units divide as follows:
3 credits in mathematical and statistical foundations,
3 credits in data and computational science,
1 credit in societal implications and opportunities,
1 elective credit to be drawn from a wide range of focused applications or deeper theoretical exploration, and
1 credit capstone experience.
We also offer an option as a 5-th Year Master's Program if you are an undergraduate at Brown. This allows you to substitute maximally 2 credits with courses you have already taken.
Master of Science in Data Science
| Semester I | ||
| DATA 1010 | Probability, Statistics, and Machine Learning | 2 |
| DATA 1030 | Hands-on Data Science | 1 |
| DATA 1050 | Data Engineering | 1 |
| Semester II | ||
| DATA 2020 | Statistical Learning | 1 |
| DATA 2040 | Deep Learning and Special Topics in Data Science | 1 |
| DATA 2080 | Data and Society | 1 |
| An appropriate 1000-level or 2000-level course to be determined by the student and approved by the program advisor. Possible courses could range from advanced mathematical methods to very specific applications of data science. | 1 | |
| Summer | ||
| DATA 2050 | Data Science Practicum 1 | 1 |
| Total Credits | 9 | |
| 1 | For their capstone experience, students will work on a project with real data, potentially in any one of the areas covered by the elective course. A faculty member from one of the four departments will oversee the capstone course, although each student may collaborate with an additional faculty member, postdoc, or industry partner on his/her project. |
For more information on admission and program requirements, please visit the following website:
https://www.brown.edu/academics/gradschool/programs/data-science