The curriculum is 33 credits of required courses and 39 credits of elective courses. The goal of the program is to provide PhD students the research training needed to move the field of data science forward and to prepare them for rewarding careers in academia and industry.
Students must complete the following required courses: DS-GA-1001, Intro to Data Science, DS-GA-1002, Probability and Statistics for Data, DS-GA-1003, Machine Learning and Computational Statistics, DS-GA-1004, Big Data, and DS-GA-1005, Inference and Representation, as well as completing Research Rotation, DS-GA 2001, six times. PhD students are also required to pass a Comprehensive Exam, the Depth Qualifying Exam (DQE), the Dissertation Proposal presentation, and the Dissertation. Students are also required to complete a teaching assignment for at least one course at the Center for Data Science by the end of the fourth year of study.