The Certificate in Data Science prepares STEM students to analyze and understand the world around them using statistics, data visualization, and machine learning. The certificate is jointly administered by the Department of Computer Science and the Department of Electrical and Computer Engineering.
The online certificate program 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 or wish to receive some training in the discipline.
Students work closely with faculty to receive training across at least five courses within the School of Engineering.
Upon successful completion of certificate requirements with grades of B- or better, students may either receive the certificate or apply for admission to the Master of Science in Data Science program. If accepted to the master's program, all graduate credits earned toward the certificate with a grade of B- or better may be transferred to apply toward master's degree requirements.
The certificate prepares students for employment in emerging field of data science and prepares students for advanced graduate study. Graduates of the program apply their training to business applications or they may provide data-driven insights that assist professionals in disciplines such as medicine, architecture, education, and more.
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.
Research/Areas of Interest: Artificial intelligence, machine learning, reinforcement learning.
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: Data Science, Machine Learning, Bayesian Methods, Deep Learning, Graph
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