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.
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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
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
Combined Degree Programs
Skills Employers Want
The M.S. in Data Science and Analytics at GVSU will develop the skills you need to land the job you want. Whether the skills are advanced or general, you will build a resume of qualifications that are sure to attract employers. The following skills correlate with those pulled from actual data science job postings.
- SQL Programming
- Business Intelligence
- Strategic Planning
- Project Management
- Agile Software Development
- Business Analytics
- Data Management
- Big Data
EMSI: Source, 2020
Deadline for fall semester is July 1; winter is November 1; spring/summer is April 1. The $30 nonrefundable application fee is waived if the applicant has previously applied to Grand Valley State University. Visit gvsu.edu/gradapply/.
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 161 or 162 or equivalent, STA 216 or equivalent
“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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