Overview
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 100% online. 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.
Scholarships Available
Some School of Engineering master's and certificate programs offer scholarships to qualified students. To receive full consideration, be sure to complete your application before the submission deadline. Contact the Office of Graduate Admissions at gradadmissions@tufts.edu for more information.
Program Highlights
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:
- Certificate Track: Perfect for individuals seeking core expertise in data science without committing to the entire Master’s of Science in Data Science program. Build a strong foundation in data science with essential undergraduate courses and two graduate courses. Earn a prestigious certificate credential in a short time frame and advance your career.
- Master’s Track: Tailored to students and professionals who aspire to enroll in the Master of Science in Data Science program. Begin with foundational undergraduate courses in math and programming and advance to two graduate courses, ensuring transferable credits and seamless enrollment into the Master of Science in Data Science program.
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.
Learning Outcomes
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:
- Use mathematical and logical techniques, including linear algebra, probability, and statistics to model complex systems, solve real-world problems, and develop novel analyses.
- Write solutions to practical data science problems in programming languages such as Python.
- Organize data structures and formulate specific, complex problems.
- Understand supervised and unsupervised machine learning.
- Employ standard machine learning models to existing data sets.
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.
Career Outcomes
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 2024 was $112,590 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.
