Data Science
Academic Program Introduction
Data science lies at the intersection of computer science, mathematics, and statistics. A student pursuing a major in data science will develop a strong foundation in all three areas and complete coursework that emphasizes their integration. By completing a concentration in an applied or theoretical field connected to data analysis, students will learn how data-driven knowledge is produced in that field, gain exposure to its foundations and language, and build the perspective needed to work on field-specific data problems.
Students who major in data science must show mastery of the data science cycle through the completion of a capstone project and poster presentation. The capstone project enables students to step back and reflect on the data science process as a whole, including data ethics and communication.
Learning goals
Develop the critical thinking needed to pose and refine questions that can be answered with data in an ethical way.
Acquire computational skills needed to tackle practical data challenges.
Gain the statistical skills needed to draw meaning from data appropriately.
Programs of Study
Data science major
Students collaborate and communicate in the context of modern data.
Course highlights
Capstone in Data Science
DS340H
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Capstone in Data Science
DS340H
Senior data science majors enroll in this course in order to meet the major’s capstone requirement. The goal is to integrate and solidify the concepts learned in previous major courses. Students will demonstrate the ability to conduct applied projects via the steps in the data science process. Students will complete the capstone with the critical thinking needed to pose and refine questions that can be answered with data in an ethical way; the statistical skills needed to draw meaning from data appropriately; the computational skills needed to tackle practical data challenges; and the ability to collaborate, communicate, and critique in the context of modern data. The course is also a chance to practice and demonstrate key technical skills, such as code sharing on github or a strong command of data science libraries in both Python and R. At the end of the course, students will have created a project or portfolio that can be shared publicly. The course must be taken for a letter grade.
Opportunities
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Quantitative Analysis Institute
Designed to expand the role of statistics and data science in research, learning, and teaching, Wellesley’s QAI offers statistical consulting on student and faculty research projects, and provides other resources and events. Employing an apprenticeship model, QAI hires student interns, who serve as statistical experts alongside the QAI director, expanding their technical knowledge and learning to communicate about data with researchers from other fields.
Beyond Wellesley
Beyond Wellesley
Many of our graduates pursue Ph.D. and master’s degrees in data science or statistics. Career fields include tech, medicine, and law, among others.
Data Science Program
106 Central Street
Wellesley, MA 02481