The ability to answer urgent and novel questions using large data sets has become increasingly important in the past decade and promises 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.<\/p>\n
To meet that need, we offer our master\u2019s students the opportunity to specialize in data-centric computing. This specialization incorporates intensive study across a spectrum of related areas\u2014including machine learning, databases, data mining, algorithms, and systems\u2014in an eight-course program. The computer science (CS) program at Boston University is geared toward students with a CS undergraduate degree, but it also welcomes those with equivalent computer training and experience, as well as students with gaps in their CS background but strong academic records overall.<\/p>\n
The MS in Computer Science with Specialization in Data-Centric Computing has the same course requirements\u2014eight graduate courses (32 units)\u2014and core breadth course requirements as the MS in Computer Science<\/a>. Of the eight courses required, five courses must fulfill the core program\u00a0breadth requirements<\/a>, with at least one in each of the following areas:<\/p>\n The remaining three courses can be fulfilled by any graduate-level CS course in data-centric computing.<\/p>\n Students are expected to achieve a grade of B\u2013 or better in all graduate-level courses that count towards the 32-degree credit requirement. In addition,\u00a0among the grades received for the five breadth courses<\/strong>, the number of grades of B\u2013 must not be greater than the number of grades of B+ or higher. No grade lower than B\u2013 may be used for graduate credit.<\/p>\n Of the eight required courses for the MS CS degree, students must take five (breadth requirement) courses, three of which satisfy the CS core and two of which satisfy the specialization requirements of the student\u2019s CS program track.<\/p>\n The\u00a0MS in CS Core Breadth Requirements<\/strong>\u00a0must be satisfied by all students pursuing an MS in CS, inclusive of specialization. This core requirement covers the three areas of\u00a0software<\/em>,\u00a0systems,<\/em>\u00a0and\u00a0theory<\/em>. Students can satisfy each area of the core with any graduate-level CS course that is applicable. However, it is recommended that the CS core be satisfied with the courses that have been explicitly designed to form the core CS foundation for master\u2019s students, specifically:<\/p>\n Students wishing to satisfy a core area with a different course, other than the course recommended, have the option to do so with the approval of their CS advisor.<\/p>\n In addition to the three course CS Core requirement, students must complete at least\u00a0two\u00a0<\/em>additional courses specific to degree.<\/p>\n Students who are in the Data-Centric Computing specialization track, should take at least two additional specialization core requirements offered in the area of data science. The data-centric computing core specialization courses<\/strong>\u00a0are:<\/p>\n *Students are only allowed to take 542 or 541 but\u00a0not<\/strong>\u00a0both within their program.*<\/p>\n The remaining three courses are fulfilled by\u00a0data-centric computing-related electives<\/strong>\u00a0in the following departments:<\/p>\n There is no foreign language requirement for this degree.<\/p>\n While not required to do so, MS candidates may complete a master\u2019s project or thesis. Projects are carried out with the approval of, and under the supervision of, a faculty member. A master\u2019s project can be expanded into a master\u2019s thesis, which requires two faculty readers.<\/p>\n","protected":false},"excerpt":{"rendered":" The ability to answer urgent and novel questions using large data sets has become increasingly important in the past decade and promises 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 […]<\/p>\n","protected":false},"author":4502,"featured_media":0,"parent":3511,"menu_order":5,"comment_status":"closed","ping_status":"closed","template":"","meta":[],"_links":{"self":[{"href":"https:\/\/www.bu.edu\/academics\/wp-json\/wp\/v2\/pages\/63800"}],"collection":[{"href":"https:\/\/www.bu.edu\/academics\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.bu.edu\/academics\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.bu.edu\/academics\/wp-json\/wp\/v2\/users\/4502"}],"replies":[{"embeddable":true,"href":"https:\/\/www.bu.edu\/academics\/wp-json\/wp\/v2\/comments?post=63800"}],"version-history":[{"count":9,"href":"https:\/\/www.bu.edu\/academics\/wp-json\/wp\/v2\/pages\/63800\/revisions"}],"predecessor-version":[{"id":97525,"href":"https:\/\/www.bu.edu\/academics\/wp-json\/wp\/v2\/pages\/63800\/revisions\/97525"}],"up":[{"embeddable":true,"href":"https:\/\/www.bu.edu\/academics\/wp-json\/wp\/v2\/pages\/3511"}],"wp:attachment":[{"href":"https:\/\/www.bu.edu\/academics\/wp-json\/wp\/v2\/media?parent=63800"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}\n
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Data-Centric Computing Track<\/h3>\n
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Language Requirement<\/h2>\n
Master\u2019s Project<\/h2>\n