Data Science

Tufts School of Engineering is uniquely positioned to offer an interdisciplinary data science program, expanding research in the field and providing students with state-of-the-art facilities to work on projects and hone their skills.

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Office of Graduate Admissions
Bendetson Hall
Medford, MA 02155
(617) 627-3395
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Data Science (M.S.)

The M.S. in Data Science is offered jointly by the departments of Computer Science and Electrical and Computer Engineering. Master's degrees require a minimum of 30 SHUs and the fulfillment of at least 10 courses at the 100-level or above with grades of S (satisfactory) or at least a B-.

The M.S. in Data Science is a program that may be completed in as little as 9 or 12 months of study. Prerequisites for the M.S. in Data Science include a bachelor's degree in a STEM field, including Mathematics, Natural or Social Science, Engineering, Computer Science, or a related discipline. Applicants with bachelor's degrees in non-STEM fields can begin study with a Certificate in Data Science that, in an additional term or year, gives the applicant a sample of the program. The courses in the certificate, upon successful completion with a grade of B- or better and admission to the M.S. in Data Science, may be transferred to apply to the M.S. in Data Science program.

Dual Degree Master's Program (with Tufts Gordon Institute)

Develop your innovation, leadership and management skills and build your technical depth with the Dual Degree Master's Program. You’ll earn two degrees: an M.S. offered jointly by the Department of Computer Science and the Department of Electrical and Computer Engineering, and an M.S. Innovation & Management (MSIM). You earn both degrees in an accelerated time frame (as little as two years) and at a reduced cost. Contact tgi@tufts.edu for more information.

Data Science (Certificate)

The Certificate in Data Science is intended for students who possess a Bachelor of Science in a Science, Technology, Engineering, or Mathematics (STEM) field, but who lack sufficient background in Data Science to be admitted to the Master of Science in Data Science. 

M.S. Curriculum

Requirements for the degree include nine courses, and must include:

  • EE 104  Probabilistic Systems Analysis (3 SHUs) or Math 165 Probability (4 SHUs)
  • Math 166 Statistics (4 SHUs)
  • CS 135 Introduction to Machine Learning and Data Mining (3 SHUs)
  • CS 119 Big Data (4 SHUs)

Four electives must include:

  1. One course in data infrastructure (including CS 112, 115, 116, 117, 118, 120, and 151)
  2. One course in data analysis and/or interfaces (including CS 136, 137, 138, 141, 142, 152, 167, 171, 175, 177, 178; ME 150; CEE 187)
  3. One course in computational and theoretical aspects of data analysis (including CS 131, 153, 160, 236; DS 153; Math 123, 125, 126, 133, 153, 156; EE 109, 127, 130, 133, 140)
  4. A final course credit may be fulfilled by a course in the practice of data science (DS 143 or 154), or a master’s project in Data Science (DS 293)

Extra SHUs – for a total of 30 – may be taken in categories A-D. The following courses may also be counted toward the SHU requirement:

  • DS 205 Principles of Data Science in Python
  • DS 295 Master's thesis in Data Science
  • DS 299 Internship in Data Science
Certificate Curriculum

The Certificate in Data Science requires five courses, including:

  • EE 104
  • CS 135
  • One elective in each of the following areas:
    • Data infrastructure (including CS 112, 115, 116, 117, 118, 119, 120, and 151)
    • Data analytics and/or interfaces (including CS 136, 137, 138, 141, 142, 152, 167, 171, 175, 177, 178, 236, 272, 275, and 277; ME 150; CEE 187)
    • Computational and theoretical aspects of data analysis (including CS 131 and 160; DS 153 or CS 153; Math 123, 125, 126, 133, 153, 155, 156, 165, and 166; EE 109, 127, 130, 133, and 140)
  • Students lacking the prerequisites for these courses must complete those prerequisites as part of the certificate; these include Math 32, 34, and 70, and CS 11, 15, and 61. DS 205 may be taken in lieu of CS 11 and 15.

 

Faculty

Alva Couch
Associate Professor
Ph.D. , Tufts University
Policy-Based Languages for System and Network Administration, Support Tools for Teaching Hands-On Computer Science
Shuchin Aeron - Associate Professor
Shuchin Aeron
Associate Professor
Ph.D. , Boston University
Technical foci: Statistical Signal Processing (SSP), Inverse Problems, Compressed Sensing, Information Theory, Convex optimization, Machine learning; Application areas: Algorithms for geophysical signal processing, Compressed Sensing architectures and evaluation, video and Image data acquisition and processing, bioengineering-metabolic networks
Lenore Cowen
Professor
Ph.D. , Massachusetts Institute of Technology
Graph Algorithms, Distributed Algorithms, Approximate Routing, Classification and Clustering For High-Dimensional Data, Coloring and Its Generalizations, Computational Molecular Biology
Bert Huang
Bert Huang
Assistant Professor
PhD , Columbia University
Machine learning, data science, structured output learning, algorithmic fairness, weak supervision
Michael Hughes - Assistant Professor
Michael Hughes
Ann W. Lambertus and Peter Lambertus Assistant Professor
Ph.D , Brown University
Machine learning, Probabilistic models, Optimization, Clinical informatics
Usman Khan
Associate Professor
Ph.D. , Carnegie Mellon University
Robotics, Signal Processing, Sensing in The Context of Distributed Estimation and Control Algorithms, Distributed, Iterative Algorithms in Random Environments
Liping Liu - Assistant Professor
Liping Liu
Schwartz Family Faculty Development Assistant Professor
Ph.D , Oregon State University
Machine learning, Graphical models, Computational sustainability
Donna Slonim
Professor
Ph.D. , Massachusetts Institute of Technology
Algorithms for Mircroarray Data Analysis, Inference of Genetic Regulatory Networks, Interpretation of Biological Experiments in the Context of Genomic and Systems Information

For deadline information, visit https://asegrad.tufts.edu/admissions/application-deadlines.

M.S. Program

Application Requirements:


> Application Fee
> Resume/CV
> Personal Statement
> Official GRE scores (if applicable)

- GRE General Test scores not required for applicants who will have received a degree from a U.S. or Canadian institution by time of enrollment. GRE scores required for all other applicants.

> Official TOEFL, IELTS, or Duolingo test scores (if applicable)
> Transcripts
> Three letters of recommendation
> Portfolio (optional)

Certificate Program

Application Requirements


> Application Fee
> Resume/CV
> Personal Statement
> Official TOEFL, IELTS, Duolingo test scores (if applicable)
> Transcripts
> One letter of recommendation

For questions about this program, including scholarships and assistantships, please contact the graduate program director.
 

Department of Computer Science
Halligan Hall
161 College Avenue
Medford, MA 02155
Office: 617-627-2225
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School of Engineering
Tufts University
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Office: 617-627-3217