MS in Computer Science with Specialization in Data-Centric Computing

The ability to answer urgent and novel questions using large data sets has become increasingly important in the past decade, and is expected to become even more prevalent in the coming years. As a result, there is considerable and growing demand for computer scientists specifically trained in methods for extracting knowledge from large data sets, and with the ability to develop computing systems and software that support that process.

To meet that need, we offer our master’s students the opportunity to specialize in data-centric computing. The specialization incorporates intensive study across a spectrum of related areas, including machine learning, databases, data mining, algorithms, and systems, in an eight-course program. The computer science (CS) program at Boston University is geared toward students with a CS undergraduate degree, but we also welcome those with equivalent computer training and experience, as well as students with gaps in their CS background but strong academic records overall.

Course Requirements

The MS in Computer Science with Specialization in Data-Centric Computing has the same course requirements—eight graduate courses (32 credits)—and core breadth course requirements as the MS in Computer Science. In particular, master’s candidates are required to complete at least five courses from the list of designated breadth (core) courses shown in the department graduate bulletin.

  • Five designated breadth courses, including at least one course in each of the following areas:
    • Theory
    • Systems
    • Software
    • Applications
  • At least two core CS data courses
  • At least three CS data-related courses
  • Up to two elective non-CAS/CS data-related graduate courses, taught in another graduate program at BU and approved by the faculty advisor

Among the grades received for the five core courses, the number of grades of B– must not be greater than the number of grades of B+ or higher. The three remaining non-core (elective) courses are determined in consultation with, and approved by, the student’s faculty advisor. No grade lower than B– may be used for graduate credit.

A CS course can be used toward satisfying multiple requirements. For example, CAS CS 542 Machine Learning can be used to satisfy both the applications breadth course requirement and the core CS data requirement, or CAS CS 530 Advanced Algorithms can be used to satisfy both the theory breadth course requirement and the CS data-related course requirement.

Language Requirement

There is no foreign language requirement for this degree.