{"id":6,"date":"2014-01-02T21:42:07","date_gmt":"2014-01-02T21:42:07","guid":{"rendered":"https:\/\/www.saintpeters.edu\/data-science-and-business-analytics\/curriculum\/"},"modified":"2026-02-20T13:10:10","modified_gmt":"2026-02-20T13:10:10","slug":"curriculum","status":"publish","type":"page","link":"https:\/\/www.saintpeters.edu\/academics\/graduate-programs\/master-of-science-in-data-science\/curriculum\/","title":{"rendered":"Curriculum"},"content":{"rendered":"

Graduate Data Science<\/h2>\n\n\n\n\n\n\n\n\n\n
At A Glance<\/td>\n<\/td>\n<\/tr>\n
Degree Awarded:<\/td>\nMaster of Science in Data Science with a Concentration in Business Analytics<\/td>\n<\/tr>\n
Concentrations:<\/td>\nBusiness Analytics<\/td>\n<\/tr>\n
Course Locations:<\/td>\nJersey City Campus<\/td>\n<\/tr>\n
Program Duration:<\/td>\n36 Credits: A full\u2010time student taking 24 credits\/year should complete in 1.5 years.<\/td>\n<\/tr>\n
Calendar:<\/td>\nGraduate Semester<\/td>\n<\/tr>\n
Course Format:<\/td>\nClasses meet in person Monday to Friday during the day or during the evening.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Vijay Voddi, M.S., Director, Master of Science in Data Science Program<\/strong><\/p>\n

Master of Science in Data Science<\/strong><\/p>\n

The Master of Science in Data Science, a 36 credit degree program, is intended for students who have completed undergraduate degrees in science, mathematics, computer science or engineering and are interested in pursuing careers in industry-specific analytical fields (e.g. technology, pharmaceutical, research, government, public health, entrepreneurship, finance, business, etc.).<\/p>\n

The Data Science degree program uses real-world problems and situations to prepare graduates for roles as strategic thought leaders who leverage predictive modeling to drive decision making. Students will develop in depth understanding of the key technologies in data science and business analytics: data mining, machine learning, visualization techniques, predictive modeling, and statistics. \u00a0Students will practice problem analysis and decision-making. Students will gain practical, hands-on experience with statistics programming languages and big data tools through coursework and applied research experiences.<\/p>\n

Program Availability<\/strong><\/h2>\n

The Data Science program will be offered on a semester schedule and is designed for both full-time and part-time study.<\/p>\n

Degree Requirements<\/h2>\n

The degree requires 36 semester hour credits. A capstone course is required and will be taken the final semester of coursework.<\/p>\n

Graduate Internship<\/h2>\n

As of January 1, 2016, completion of an internship related to Data Science is required for all students except: those who have 3+ years of professional work experience; those with full-time employment during the length of the program; and those who are participating in the exchange program. The graduate internship can start in the fourth trimester of classes. Please consult your program advisor to determine if it is possible to obtain a waiver.\u00a0<\/p>\n

Advisement<\/h2>\n

Â鶹´«Ã½AVÂ鶹´«Ã½AV assigns an academic advisor to every candidate.<\/p>\n

Time Limitation<\/h2>\n

Students are expected to enroll continuously until their programs are completed. \u00a0Students are required to maintain satisfactory academic progress by maintaining the required grade point average and accumulating sufficient credits within the stipulated time frame of five years.\u00a0By federal regulation, F-1 International students must enroll as full-time students, so their time to completion will be considerably shorter.<\/p>\n

Curriculum - Master of Science in Data Science - Traditional track<\/h2>\n

The Master's in Data Science program is divided into two levels as detailed below.\u00a0<\/p>\n<\/colgroup>
Required Core Courses<\/span><\/td>27<\/td><\/tr>\n
DS-510<\/span><\/div><\/td>
Intro to Data Science and AI<\/td><\/td><\/tr>\n
DS-520<\/span><\/div><\/td>
Data Analysis and Decision Modeling<\/td><\/td><\/tr>\n
DS-530<\/span><\/div><\/td>
Data Management Systems<\/td><\/td><\/tr>\n
DS-542<\/span><\/div><\/td>
Python in Data Science<\/td><\/td><\/tr>\n
DS-600<\/span><\/div><\/td>
Data Mining<\/td><\/td><\/tr>\n
DS-620<\/span><\/div><\/td>
Data Visualization<\/td><\/td><\/tr>\n
DS-630<\/span><\/div><\/td>
Machine Learning<\/td><\/td><\/tr>\n
DS-650<\/span><\/div><\/td>
Data Ethics and Artificial Intelligence<\/td><\/td><\/tr>\n
DS-670<\/span><\/div><\/td>
Capstone: Big Data & Data Science<\/td><\/td><\/tr>\n
Electives - Take 3 courses from the following:<\/span><\/td>9<\/td><\/tr>\n
DS-610<\/span><\/div><\/td>
Big Data Analytics<\/td><\/td><\/tr>\n
DS-640<\/span><\/div><\/td>
Predictive Analytic & Financial Modeling<\/td><\/td><\/tr>\n
DS-660<\/span><\/div><\/td>
Business Analytics<\/td><\/td><\/tr>\n
DS-680<\/span><\/div><\/td>
Marketing Analytics & Operation Research<\/td><\/td><\/tr>\n
DS-690<\/span><\/div><\/td>
Data Science and Health<\/td><\/td><\/tr>\n
Industry Experience- Complete after 4th trimester<\/span><\/td><\/td><\/tr>\n
DS-597<\/span><\/td>Applied Research Experience<\/td>0<\/td><\/tr>\n
or\u00a0DS-598<\/span><\/td> Applied Industry Experience<\/td><\/tr>\n
DS-595<\/span><\/td>Applied Work Experience CPT-Traditional<\/td>1<\/td><\/tr>\n
Total Credits<\/td>37<\/td><\/tr><\/tbody><\/table>\n

Data Science Graduate Internship<\/h3>\n

Completion of a graduate internship related to Data Science is required for all students except: those who have 3+ years of professional work experience; those with full-time employment during the length of the program; and those who are participating in an exchange program. The graduate internship must start in the first semester of classes. Please consult your program adviser to determine if it is possible to obtain a waiver.<\/p>\n","protected":false},"excerpt":{"rendered":"

Graduate Data Science At A Glance Degree Awarded: Master of Science in Data Science with a Concentration in Business Analytics Concentrations: Business Analytics Course Locations: Jersey City Campus Program Duration: 36 Credits: A full\u2010time student taking 24 credits\/year should complete in 1.5 years. Calendar: Graduate Semester Course Format: Classes meet in person Monday to Friday […]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":15,"comment_status":"closed","ping_status":"closed","template":"template-department-standard-child.php","meta":{"_acf_changed":false,"footnotes":""},"class_list":["post-6","page","type-page","status-publish","hentry"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.saintpeters.edu\/academics\/graduate-programs\/master-of-science-in-data-science\/wp-json\/wp\/v2\/pages\/6","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.saintpeters.edu\/academics\/graduate-programs\/master-of-science-in-data-science\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.saintpeters.edu\/academics\/graduate-programs\/master-of-science-in-data-science\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.saintpeters.edu\/academics\/graduate-programs\/master-of-science-in-data-science\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.saintpeters.edu\/academics\/graduate-programs\/master-of-science-in-data-science\/wp-json\/wp\/v2\/comments?post=6"}],"version-history":[{"count":21,"href":"https:\/\/www.saintpeters.edu\/academics\/graduate-programs\/master-of-science-in-data-science\/wp-json\/wp\/v2\/pages\/6\/revisions"}],"predecessor-version":[{"id":12020,"href":"https:\/\/www.saintpeters.edu\/academics\/graduate-programs\/master-of-science-in-data-science\/wp-json\/wp\/v2\/pages\/6\/revisions\/12020"}],"wp:attachment":[{"href":"https:\/\/www.saintpeters.edu\/academics\/graduate-programs\/master-of-science-in-data-science\/wp-json\/wp\/v2\/media?parent=6"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}