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Data Science

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 1010Probability, Statistics, and Machine Learning2
DATA 1030Hands-on Data Science1
DATA 1050Data Engineeriing1
Semester II
DATA 2020Statistical Learning1
DATA 2040Deep Learning and Special Topics in Data Science1
DATA 2080Data and Society1
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 2050Data Science Practicum 11
Total Credits9

For more information on admission and program requirements, please visit the following website:

https://www.brown.edu/academics/gradschool/programs/data-science

Professor

R. Bahar
Professor of Computer Science; Professor of Engineering

Ugur Cetintemel
Professor of Computer Science

Eugene Charniak
University Professor of Computer Science

Thomas L. Dean
Professor Emeritus of Computer Science

Amy R. Greenwald
Professor of Computer Science

Maurice P. Herlihy
An Wang Professor of Computer Science

John F. Hughes
Professor of Computer Science

Sorin Istrail
Julie Nguyen Brown Professor of Computational and Mathematical Science

Philip Klein
Professor of Computer Science

Shriram Krishnamurthi
Professor of Computer Science

David H. Laidlaw
Professor of Computer Science

Michael L. Littman
Professor of Computer Science

Anna A. Lysyanskaya
Professor of Computer Science

Franco Preparata
An Wang Professor Emeritus of Computer Science

Steven P. Reiss
Professor of Computer Science

John E. Savage
An Wang Professor Emeritus of Computer Science

Roberto Tamassia
Plastech Professor of Computer Science

Gabriel Taubin
Professor of Computer Science; Professor of Engineering

Eliezer Upfal
Rush C. Hawkins University Professor of Computer Science

Andries van Dam
Thomas J. Watson Jr. University Professor of Technology and Education, Professor of Computer Science

Stanley B. Zdonik
Professor of Computer Science

Professor Research

Kathi Fisler
Professor of Computer Science (Research)

Associate Professor

Rodrigo Fonseca
Associate Professor of Computer Science

Seny F. Kamara
Associate Professor of Computer Science

Stefanie A. Tellex
Associate Professor of Computer Science

Associate Professor Research

Thomas W. Doeppner
Associate Professor of Computer Science (Research)

Assistant Professor

Stephen Bach
Assistant Professor of Computer Science

Theophilus A. Benson
Assistant Professor of Computer Science

Carsten Eickhoff
Assistant Professor of Computer Science; Assistant Professor of Medical Science

Jeff Huang
Assistant Professor of Computer Science

Vasileios Kemerlis
Assistant Professor of Computer Science

George D. Konidaris
John E. Savage Assistant Professor of Computer Science

Ellie Pavlick
Assistant Professor of Computer Science

Daniel C. Ritchie
Assistant Professor of Computer Science

Malte Schwarzkopf
Assistant Professor of Computer Science

Ritambhara Singh
Assistant Professor of Computer Science

James H. Tompkin
Assistant Professor

Assistant Professor Research

Tim Nelson
Assistant Professor of Computer Science (Research)

Senior Lecturer

Barbara J. Meier
Senior Lecturer in Computer Science

Lecturer

Doug Woos
Lecturer in Computer Science

Adjunct Professor of the Practice

Linn F. Freedman
Adjunct Professor of the Practice of Computer Science

Norm Meyrowitz
Adjunct Professor of the Practice of Computer Science

Adjunct Associate Professor

Tim Klas Kraska
Adjunct Associate Professor of Computer Science

Adjunct Assistant Professor

John H. Jannotti
Adjunct Assistant Professor of Computer Science

Visiting Scientist

Matteo Riondato
Visiting Scientist in Computer Science