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Professor Scott Frees working with a student

Master of Science in Data Science (MSDS)

Data Science sits at the intersection of mathematics and computer science and is applied to a boundless set of disciplines – including health, physical sciences, business, environmental studies, sociology, and political science. Pricewaterhouse Coopers has estimated that 27% of employers are looking for a Master’s degree when filling Data Science positions. That same study identifies New Jersey and New York as the #1 region in terms of number of job postings.

The Master of Science in Data Science degree will prepare graduates with sought-after skills in programming, statistics, machine learning, and data visualization – providing opportunities to pursue high-paying, high-quality jobs at some of the most influential and prestigious companies in the country.

MSDS students complete 10 courses (30 credits), including a thesis. Full time students complete their degree in two years, however part-time students are accepted as well. Courses are delivered as a combination of online, hybrid, and evening in-seat format.

  • Current Ramapo students in Computer Science, Mathematics, Bioinformatics, or Data Science may also be eligible to complete the 4+1 MSDS program and earn their M.S. in their 5th year at Ramapo.
  • International Students: F-1 nonimmigrant students graduating with an MS in Data Science are eligible for the DHS’s STEM OPT program. Please contact Rajesh Adhikari, Office of International Student and Scholar Services at radhikar@ramapo.edu to discuss any immigration issues and concerns.
  • GRE scores are not required. Applications are evaluated based on work experience, undergraduate GPA, and recommendation letters.

Undergraduate Enrollment

In some cases, undergraduates are permitted to enroll in MSDS courses. Students who are enrolled in the 4+1 BS to MS Data Science program may take up to 3 graduate courses while completing their Bachelor’s degree. Students not enrolled in the 4+1 program are limited to two courses.

Undergraduates not enrolled in the 4+1 program are subject to the following requirements for enrolling in MSDS courses:

  • You must have already completed 96 credits towards your undergraduate degree
  • You must have a GPA of 3.0 or greater
  • You must receive permission from the Program Director (sfrees@ramapo.edu), which will be subject to review of your previous coursework to ensure you are prepared for the course you wish to enroll in.
  • Finally, graduate students and 4+1 undergraduates are given priority in situations where a section is reaching it’s maximum capacity. The Program Director may reserve seats in anticipation of graduate or 4+1 students.


Ramapo

To begin MSDS coursework, students must have basic skills in computer programming, statistics, and linear algebra. To remain in good academic standing, students must maintain a cumulative GPA of 3.0.

Data Science – (9 credits)

Computer Science – (6 credits)

Mathematics – (6 credits)

Electives (9 credits)

Students must complete two technical electives and one interdisciplinary elective. DATA 730 Fieldwork Experience may be used to replace one of the three total electives. Click the links below to see lists of courses in each category.

2-Year Plan (Full-time students)

Courses are offered either in an online format or during the evenings to accommodate students currently working.

1st Semester

2nd Semester

3rd Semester

4th Semester

Students are encouraged to enroll in the summer and winter online course offerings for the above requirements when available. DATA 730 – Fieldwork Experiences, which may count towards an elective, is also frequently offered during the summer session.

Students enrolled in Computer Science, Bioinformatics, Mathematics, and Data Science undergraduate 4-year degrees may be eligible for the 4+1 MSDS program.

Ramapo

Program Director

Scott Frees
Professor of Computer Science

Year Joined RCNJ: 2006
Phone: (201) 684-7726
Email: sfrees@ramapo.edu
Office: G-315
Office Hours: via WebEx by appointment
Personal Website