2021-2022 Undergraduate & Graduate Catalog

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Master of Science in Data Science and Analytics

• Admission
• PSM Courses

The M.S. in data science and analytics is one of five synergistic professional science master's (PSM) degree programs at Grand Valley State University. The five programs (applied statistics, biostatistics, cell and molecular biology (biotechnology), data science and analytics, and health informatics and bioinformatics) are interdisciplinary and involve both the university and its industry partners. All five programs emphasize teamwork, problem-solving, communication, scientific knowledge, and technical skills. Each program is designed to integrate university coursework with business/industrial internships to better prepare students for the variety of career pathways associated with the life science and health science industries. The overall objectives and interactions of these five programs are described in the PSM section of the Grand Valley State University Undergraduate and Graduate Catalog.

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 the following:

• 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.

Admission

In addition to Grand Valley's admission requirements, all students seeking the M.S. degree in data science and 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 from two professional or academic references received online, addressing the candidate's potential for graduate study completion. You will provide the emails of two references in your account at 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

Requirements

CIS Courses

A total of four courses (12 credits) are required, including:

• CIS 635 - Knowledge Discovery and Data Mining (3 credits)
• CIS 660 - Information Management and Science (3 credits)
• CIS 671 - Information Visualization (3 credits)

PLUS one of the following:

• CIS 677 - High-performance Computing (3 credits)
• CIS 678 - Machine Learning (3 credits)

Statistics Courses

A total of four courses (12 credits) are required, including:

• STA 518 - Statistical Computing and Graphics with R (3 credits)
• STA 616 - Statistical Programming (3 credits)
• STA 631 - Statistical Modeling and Regression (3 credits)

PLUS one of the following:

• STA 526 - Multivariate Data Analysis (3 credits)
• STA 623 - Categorical Data Analysis (3 credits)

Electives Course

One elective course approved by an advisor for a total of three credits is required.

PSM Courses

The following courses are required:

• PSM 650 - Ethics and Professionalism in Applied Science (3 credits)
• PSM 662 - Seminar in Professional Science Practice (2 credits)
• PSM 691 - Internship (1 to 9 credits)