The Data Science master's program trains students to use statistics, data visualization, and machine learning to analyze and understand the world around them. The master's program is jointly administered by the Department of Computer Science and the Department of Electrical and Computer Engineering.
The Data Science master's program is built upon a disciplinary core of statistics and machine learning, with depth provided by courses in each of the following categories:
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. Learn more about the Co-Op Program.
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.
Prerequisites for the Data Science master's program include a Bachelor of Science degree in a science, technology, engineering, or mathematics (STEM) field. Applicants with Bachelor's degrees in non-STEM fields may begin study with a Certificate in Data Science that‚ in an additional term‚ gives the applicant a sample of the program.
We recognize that attending graduate school involves a significant financial investment. Our team is here to answer your questions about tuition rates and scholarship opportunities.
Please contact us at gradadmissions@tufts.edu.
Average Salary: $108K+
Projected Job Growth (2022-2032): 35%
*Sources: Average salary and projected job growth statistics are from the U.S. Bureau of Labor Statistics Occupational Outlook Handbook.
Research/Areas of Interest: data science, software systems engineering, performance analysis, system, network, and data management
Research/Areas of Interest: data science, statistical signal processing, inverse problems, compressed sensing, information theory, convex optimization, machine learning, algorithms for geophysical signal processing, compressed sensing architectures and evaluation, video and image data acquisition and processing
Research/Areas of Interest: computational molecular biology, data science, graph algorithms, network science, discrete mathematics
Research/Areas of Interest: Machine learning : probabilistic models, Bayesian inference, variational methods, time-series analysis, semi-supervised learning Clinical informatics : electronic health record analysis
Research/Areas of Interest: Optimization and Control, Machine Learning, Signal Processing, Graph Theory, Decentralized Algorithms
Research/Areas of Interest: Machine Learning, Data Science, Deep Learning, Generative Models, Time Series, Graph Learning
Research/Areas of Interest: data science, algorithms for analysis of biological networks, gene and pathway regulation in human development, algorithms for precision medicine, computational approaches to pharmacogenomics and drug discovery or repositioning