Participants will gain a fundamental understanding of the methods and algorithms of data science, through study of relevant topics in mathematics, statistics and computer science, including machine learning, data mining, visualization, and data management. The program will also provide experience in important, frontline data science problems in a variety of fields, and introduce students to ethical and societal considerations surrounding data science and its applications. This rigorous knowledge will position them for high-level and leadership placement in academic and industrial arenas where data science plays a key role.
Brown Ph.D. students who enter the certificate program will be required to have completed at least a year of calculus (at the level of MATH 0090 & 0100), a semester of linear algebra (at the level of MATH 0520), a semester of calculus-based probability and statistics (at the level of APMA 1650), and an introduction to programming (at the level of CSCI 0150 or 0170). Because of the integrative character of the program, we look to accept students from a variety of backgrounds and disciplines. Prospective applicants who lack one or more of the prerequisites may contact us for help with discussing options for fulfilling them.
The graduate specialization certificate is comprised of 5 credits:
- 2 credits on mathematical and statistical foundations (APMA 1690 or CSCI1450, DATA 2060 or CSCI1420)
- 2 credits on computational science (DATA 1030, 1050)
- 1 credit on societal implications and opportunities (DATA/CSCI1951Z, Fairness in Automated Decision-Making)