Data Science and Analytics, M.S.
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 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.
Why Study Data Science and Analytics at Grand Valley?
- Demand. The number of job postings for data science grew 57 percent for the first quarter of 2017. Data-related jobs are expected to grow by 11 percent from 2014 to 2024, according to the Bureau of Labor Statistics.
- Flexibility. This program is designed with the working professional in mind, and offers classes in the evening.
- Experiential learning. The program includes field experiences and collaborative assignments and projects.
- First-rate faculty. Passionate practitioners with years of experience in the field.
- Core fundamentals. The degree has a strong emphasis in the fundamentals of data science.
For More InformationSchool of Computing and Information Systems
C-2-100 Mackinac Hall, (616) 331-2060Graduate Admissions
Deadline for fall semester July 1; winter November 1; and spring/summer April 1. The $30 nonrefundable application fee is waived if the applicant has previously applied to Grand Valley State University. Visit gvsu.edu/gradapply/.
Location & Format
Classes for graduate students in this major meet downtown on the Robert C. Pew Grand Rapids Campus.Format: Face To Face
The program consists of:
- Four courses in computer information systems
- Four courses in statistics
- Three professional science courses, including an internship
- One elective course
Students are expected to complete field experiences and collaborative assignments and projects.
Students will go on to have successful careers in:
- Finance and insurance
- Knowledge storage and retrieval
- National security
- Political science and polling
- Public transportation and safety
- Science and analytics
- Social media analytics
“What abilities make a data scientist successful? Think of him or her as a hybrid of data hacker, analyst, communicator, and trusted adviser. The combination is extremely powerful, and rare... A good data scientist will have many doors open to him or her, and salaries will bid upward.”
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