Data Science, Graduate Certificate

Graduate Business Programs
238 Elliott Hall (map)
(248) 370-3287
OUgradbusiness@oakland.edu
http://www.oakland.edu/business/grad

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Program Director:
Paul Trumbull
238B Elliott Hall
(248) 370-3277
trumbull@oakland.edu

Program Description

This program focuses on understanding big data as well as developing analytical and technical skills to support data-driven decision making. It is interdisciplinary in nature and designed to provide students from different majors the ability to solve complex problems through the backdrop of data science. Students will explore through hands-on practical experiences various topics such as statistical analysis, machine learning, and big data analytics. The goal of the program is to explicitly augment the focused discipline-specific education of Science, Technology, Engineering, the Arts and Mathematics (STEAM) graduate students with data science skills. This graduate certificate is ideal for the working professional in any field who is looking to gain knowledge in data science.

Admission terms and application deadlines

Before an applicant’s file can be reviewed for full program admission, all application documents must be received at Oakland University Graduate School by the semester deadlines listed below. Incomplete applications will not be sent to departments for admission review.

July 15 for fall semester
November 15 for winter semester
March 1 for summer semester

International Applicants

May 1 for fall (September) admission
September 1 for winter (January) admission
January 1 for summer (May) admission

Application requirements

To be considered for graduate admission, applicants must submit all Graduate Application Requirements and additional department requirements by the published application deadlines:

Graduate Application Requirements
Additional department application requirements

An earned baccalaureate degree from a regionally accredited institution OR a degree equivalent to a four-year U.S. baccalaureate degree from a college or university of government-recognized standing.
Curriculum Vitae or Resumé

Admission review and assessment

Admission to the Graduate Certificate in Data Science program is selective. In making admission recommendations to the graduate certificate program, the department assesses the potential of applicants for success in the program by examining their graduate records, their responses to questions on the Supplemental Program Form, their experience, and their recommendation forms.

Certificate prerequisites

Personal Computer (PC) skills: students will be required to have proficiency in the use of word processors, spreadsheets, graphics, database management systems, and the Internet. If a student is deficient in these skills, the student would be required to take a college course, workshop, or continuing education course in PC skills as a prerequisite to the program.

Foundation Course (6 credits)

Students are expected to have some background in statistics as well as computing/programming through one or more courses in their undergraduate degree. Students lacking statistics knowledge will be required to take the foundation course QMM 5100. Similarly, students lacking the computing/programming knowledge will be required to take MIS 5240. These courses will not count towards the certificate program.

For students with the required background through prior course work, the foundation courses will be waived.

QMM 5100 - Quantitative Methods for Managers (3 credits)
MIS 5240 - Enterprise Information Systems (3 credits)

Certificate requirements

The Graduate Certificate in Data Science is awarded upon satisfactory completion of a minimum of 16 graduate-level credits in an approved program of study.

Course requirements (16 to 18 credits)

Required core courses (10 credits)

SDS 5005 - Statistical analyses in Big Data applications (4 credits
MIS 5560 - Introduction to Data Science (3 credits)
MIS 5470 - Practical Computing for Data Analytics (3 credits)

Elective courses (6 to 8 credits)

Choose two from the following approved elective courses:
BIO 5412 - Functional Genomics and Bioinformatics (4 credits)
MIS 5600 - Deep Learning and Text Analytics (3 credits)
STA 5221 - Multivariate Statistical Methods I (4 credits)
MIS 5040 - Introduction to Databases and Data Warehousing (3 credits)
MIS 5460 - Business Analytics (3 credits)
MIS 6060 - Advanced Databases and Big Data Management (3 credits)
PSY 5102 - Advanced Statistics for Psychological & Behavioral Research II (4 credits)
PSY 5991 - Advanced Topics in Statistics for Psychological and Behavioral Research (4 credits)
PH 5410 - Biostatistical Methods in Public Health (3 credits)
PH 5450 - Applied Biostatistics in Public Health ( 3 credits)
Other analytics/quantitative Graduate electives from related disciplines (with prior approval)

Satisfactory academic progress

Satisfactory Academic Progress (SAP) is the term used to denote a student’s successful completion of coursework toward a certificate or degree. Federal regulations require the Office of Financial Aid to monitor Satisfactory Academic Progress for all financial aid recipients each semester.

Students who fall behind in their coursework, or fail to achieve minimum standards for grade point average and completion of classes, may lose their eligibility for all types of federal, state and university aid. Contact the Office of Financial Aid for additional details.

Good academic standing

All graduate students are expected to remain in good academic standing throughout the entire course of their graduate program. To be in good academic standing , a graduate student must make satisfactory progress toward fulfilling degree requirements, including the completion of critical degree milestones as set forth by the academic program. The student must also maintain a minimum semester and overall GPA of 3.0 (B) or better.

Good academic standing is a requirement for:

Holding a Graduate Assistantship
Receiving a fellowship or scholarship
Advancing to candidacy for a graduate degree
Going on a leave of absence
Obtaining a graduate certificate or degree from Oakland University.

Additionally, graduate students must meet all department academic standards which may be more stringent than the minimum set forth by the University.

Department requirements: To qualify for the graduate certificate, the student must complete the designated set of courses with a grade of 3.0 or above in each course.

Graduate students who are not in good academic standing for any reason are subject to probation and/or dismissal from further graduate study.

Related program information

Plan of study

All accepted applicants, in consultation with their assigned faculty program adviser, must develop a plan of study that details specific courses the students will use to satisfy their degree requirements. The plan of study must be approved by the faculty program adviser and submitted by the student to Oakland University Graduate School.

Master’s and graduate certificate students must submit a department-approved plan of study by the end of their first semester of graduate coursework. Doctoral students must submit an approved plan of study prior to completion of the first year of coursework. (See the Graduate Student Responsibility section of this catalog.)

Note: Credit granted for successful completion of a course toward an undergraduate degree program may not be repeated for a graduate degree. If a substitution is approved, the minimum number of program-approved graduate credits will be required. A Petition of Exception - OU Course Waiver/ Substitution requesting the substitution must be approved.

Time limits
All graduate certificate students are expected to complete their degree within the time limit established by the University .