Master of Science (M.S.) in Data Science and Analytics at Grand Valley State University

The Data Science and Analytics (M.S.) degree provides students with the fundamental analytics background necessary to work with big and complex data sets in any discipline. It also allows a statistics or computing student to gain additional cross-disciplinary background, or for a student of any discipline to develop skills to solve data-intensive problems. This degree has applications to health, social, political, and environmental issues as science and technology disciplines. It provides training in key technical areas while also developing business and communication skills.

The Data Science and Analytics (M.S.) degree is located in the School of Computing and Information Systems, within the Padnos College of Engineering and Computing. This program also collaborates closely with the Statistics Department.


Why Study Data Science and Analytics at Grand Valley?

  • In-Demand. The number of job postings for data science grew 57% for the first quarter of 2017 as compared to the first quarter of 2016.
  • Job Growth. Data-related jobs are expected to grow by 11% from 2014 to 2024 according to the Bureau of Labor Statistics.
  • Flexibility. This program is designed with the working professional in mind, and offers face-to-face classes in the evening.
  • Experiential Learning. The program includes field experiences and collaborative assignments and projects.
  • First-rate Faculty. Passionate faculty practitioners with years of experience in the field.
  • Core Fundamentals. The degree has a strong emphasis in the fundamentals of data science.
  • Data Scientist: The Sexiest Job of the 21st Century - Harvard Business Review


Courses Offered

The Data Science and Analytics (M.S.) program requires a minimum of 36 credits. Requisite courses, from statistics, computer science, and professional science, provide students with a strong foundation in data science. This is an applied program for the working professional.

The program features:

  • Four courses in computer information systems
  • Four courses in statistics
  • One elective
  • Three Professional Science courses (including an internship)

Students are expected to complete field experiences and collaborative assignments and projects.

See the full course list.


Career Opportunities

Graduates of the GVSU Data Science and Analytics (M.S.) hold position titles, such as data scientist, data engineer, business analyst, data analyst, and data developer. They will go on to have successful careers in:

  • Marketing
  • National security
  • Knowledge storage and retrieval
  • Social media analytics
  • Public transportation and safety
  • Science and analytics
  • Political science and polling
  • Finance and insurance
  • Professional services
  • And more

Admission Requirements

In addition to Grand Valley's admission requirements all students seeking a degree for the M.S. in Data Science & Analytics must also meet the following requirements:

  • Grade point average of 3.0 (B) from all undergraduate coursework or a satisfactory score on the GRE or GMAT test
  • Resume detailing work experiences and accomplishments
  • Personal statement of career goals and background experiences, including an explanation of how this program will help achieve educational and professional objectives
  • Recommendations: two professional or academic recommendations received online, addressing the candidate's potential for graduate study completion. You will provide the emails of two references in your account at www.gvsu.edu/gradapply and they will be sent a link to fill out for their online recommendation
  • Prerequisite courses: CIS 500 or equivalent, STA 216 or equivalent

The $30 application fee is waived for previous applicants of Grand Valley.


Cost

The current cost per credit hour is $657. For more information on tuition and fees, please visit the costs portion of the GVSU Financial Aid website. For financial support, scholarship search, and filing for FAFSA, please visit the GVSU Financial Support website.




Page last modified September 5, 2017