Tufts University - School of Engineering
MSc in Data ScienceDURATION
1 up to 2 Years
LANGUAGES
English
PACE
Full time, Part time
APPLICATION DEADLINE
02 Aug 2025*
EARLIEST START DATE
Sep 2025
TUITION FEES
USD 1,799 / per credit
STUDY FORMAT
Distance Learning, On-Campus
* Aug 1 (domestic only), Mar 15 (international)
Key Summary
Introduction
The master's program is jointly administered by the Department of Computer Science and the Department of Electrical and Computer Engineering.
The program is built upon a disciplinary core of statistics and machine learning, with depth provided by courses in each of the following categories:
- Data infrastructure and systems: systems and strategies that are core to interacting with data, including computer networks, computer security, internet-scale systems, cloud computing, and others.
- Data analysis and interfaces: components of computing concentrated around effective human interaction with computers, including human-computer interaction, graphics, visualization, and others.
- Computational and theoretical aspects of data science: mathematical foundations, including information theory, signal and image processing, and numerical analysis.
- Practice of data science: examples of effective use of data science in practice, including case studies and applications of data science principles to real-world problems.
Graduate Cooperative Education (Co-Op) Program
The School of Engineering's Graduate Cooperative Education (Co-Op) Program provides students with the opportunity to apply the theoretical principles they have learned in their coursework to real-world engineering projects. Gain up to six months of full-time work experience, build your resume, and develop a competitive advantage for post-graduation employment.
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Admissions
Curriculum
The Data Science program at Tufts prepares students to address real-world problems with data-centric insights. Students engage in a variety of data analysis techniques, including machine learning, optimization, statistical decision-making, information theory, and data visualization. Graduates of the program go on to work on interdisciplinary projects with data components including communicating with engineers, scientists, businesses, computer scientists, and medical professionals.
One way of completing the program is as follows:
FALL TERM
- Electrical Engineering 104 Probabilistic Systems Analysis
- Computer Science 135 Introduction to Machine Learning
- Computer Science 119 Big Data
- Data science elective (Data Infrastructure)
SPRING TERM
- Mathematics 166 Statistics
- Data science elective (Data Analysis and/or Interfaces)
- Data science elective (Computational and Theoretical Aspects of Data Analysis)
- Data science elective (Project or Practice in Data Science)
SPRING OR SUMMER TERM
- Computer Science 154 Special topics in the practice of Data Science
- or Data Science 293/Computer Science 283 Master’s project in Data Science