A completed graduate program application.<\/p>\n
It is recommended that students have a strong background in science, computer science\/programming, mathematics, statistics, applied sciences or quantitative business. Applicants are evalsuated on an individual basis and may be required to take needed prerequisite coursework.<\/p>\n
Official transcript evidencing an earned Bachelor\u2019s and\/or Master\u2019s degree.<\/p>\n
A recommended minimum undergraduate cumulative GPA of 3.2 on a 4.0, with a recommended grade of a B or better in Calculus or equivalent course.<\/p>\n
One letter of recommendation from a professor or an employer.<\/p>\n
A personal statement describing why the applicant desires this data science degree. The statement should demonstrate: a. Strong writing skills; b. An expressed desire to work in the represented field; c. A strong ability to reason; and d. Commitment to completing the degree.<\/p>\n
Resume of professional work experience<\/p>\n
All candidates must interview with the Director of the Data Science Institute as part of the admission process.<\/p>\n
Saint Peter\u2019s MS programs alumni are eligible to transfer in up to a maximum of eighteen (18) credits towards the program. A maximum of twelve (12) graduate credits of equivalent course work could be transferred from other accredited universities.<\/strong><\/p>\n","protected":false},"excerpt":{"rendered":" Start Terms: Spring or Fall Trimester Additional Requirements A completed graduate program application. It is recommended that students have a strong background in science, computer science\/programming, mathematics, statistics, applied sciences or quantitative business. Applicants are evalsuated on an individual basis and may be required to take needed prerequisite coursework. Official transcript evidencing an earned Bachelor\u2019s […]<\/p>\n","protected":false},"author":102,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"template-department-home.php","meta":{"_acf_changed":false,"footnotes":""},"class_list":["post-17","page","type-page","status-publish","hentry"],"acf":[],"_links":{"self":[{"href":"https:\/\/huangshizhaopin.com\/academics\/graduate-programs\/phd-data-science\/wp-json\/wp\/v2\/pages\/17","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/huangshizhaopin.com\/academics\/graduate-programs\/phd-data-science\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/huangshizhaopin.com\/academics\/graduate-programs\/phd-data-science\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/huangshizhaopin.com\/academics\/graduate-programs\/phd-data-science\/wp-json\/wp\/v2\/users\/102"}],"replies":[{"embeddable":true,"href":"https:\/\/huangshizhaopin.com\/academics\/graduate-programs\/phd-data-science\/wp-json\/wp\/v2\/comments?post=17"}],"version-history":[{"count":4,"href":"https:\/\/huangshizhaopin.com\/academics\/graduate-programs\/phd-data-science\/wp-json\/wp\/v2\/pages\/17\/revisions"}],"predecessor-version":[{"id":35,"href":"https:\/\/huangshizhaopin.com\/academics\/graduate-programs\/phd-data-science\/wp-json\/wp\/v2\/pages\/17\/revisions\/35"}],"wp:attachment":[{"href":"https:\/\/huangshizhaopin.com\/academics\/graduate-programs\/phd-data-science\/wp-json\/wp\/v2\/media?parent=17"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}