Whether you're a recent graduate or a seasoned professional looking to transition into data science, our program is designed to accommodate learners at all stages. Recommended for those with an interest in mathematics, statistics, or computer science, the Post-Baccalaureate Certificate in Data Science provides foundational courses to kickstart your career in this dynamic field or pursue advanced studies. No prior educational background experience in data science is required.
The post-baccalaureate program is offered via two modalities – 100% online or on-campus. Either way, you’ll develop skills in data analysis and problem-solving through hands-on projects. Prepare for a successful career in data science by joining our collaborative community of students and faculty.
Data science has the potential to shape our lives in ways that we are only beginning to understand. In an increasingly data-driven world, organizations rely on harnessing facts, trends, and statistics to inform decision-making and problem-solving. The ability to organize data, interpret its meaning, and communicate actionable insights is a valuable skill that everyone can bring to their work – and the post-baccalaureate program provides the ‘on-ramp’ that all professionals need to make impactful, data-driven decisions.
Choose between two distinct paths based on your professional goals:
Both tracks consist of four fundamental undergraduate courses in mathematics and programming. Those courses are followed by two graduate courses–probability theory and fundamentals of applied machine learning–providing a strong intellectual base for success in the field.
As a student in either track of the post-baccalaureate program, you will dig deeper into key data science concepts and, upon completion, be prepared to:
Students in the Master’s Track will gain additional training in areas such as applying statistics to practical data analysis, analyzing large data sets, and exposure to various issues in data infrastructure.
The post-baccalaureate curriculum emphasizes innovation and discovery, preparing you to pursue multiple job opportunities and research projects, advance within your current organization, and increase your earning potential.
According to the U.S. Bureau of Labor Statistics, data science job opportunities are expected to grow 35% by 2032. The median salary for a data scientist in 2022 was $103,500 per year.
Possible jobs for post-baccalaureate and master’s degree graduates include data science manager, database architect, machine learning engineer, analytics manager, data scientist, data engineer, statistician, and database administrator.
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, 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: Photon-counting imaging, wavefront sensing, low-light passive imaging.
Research/Areas of Interest: data science, software systems engineering, performance analysis, system, network, and data management
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: Artificial Intelligence, Developmental Robotics, Computational Perception, Robotic Manipulation, Machine Learning, Human-Robot and Human-Computer Interaction
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