Nov 21, 2024

2024-2025 Undergraduate Catalog

Data Science, B.S.

The program in Data Science leading to a Bachelor of Science degree prepares students for a productive career in the industry and for graduate studies in diverse disciplines. The curriculum integrates quantitative analysis and computer science, setting it apart from other fields. Through hands-on projects and practical exploration of programming languages like Python and R, students delve into machine learning algorithms, data visualization techniques, and database management, gaining invaluable insights into complex dataset analysis. The curriculum places a strong emphasis on data ethics, ensuring graduates are adept at responsibly navigating diverse contexts. Capstone projects encourage the application of knowledge to solve complex problems, fostering critical thinking and innovation. With a strong focus on professional development, including technical communication and teamwork, the program ensures that graduates are well-prepared for a dynamic career in data science, equipping them with the skills and knowledge needed to excel in the rapidly evolving field.

Schedule of Classes

Specific offerings for each semester may be found in the Schedule of Classes.

Program educational objectives

In the course of their careers, graduates of the Data Science program will:

Work productively to design, implement, and improve solution to data problems.
Remain current in their profession through lifelong learning, including graduate school.
Exhibit teamwork and leadership as well as exercise their profession with the highest level of ethics and social responsibility.

Requirements for the Bachelor of Science in Data Science

To earn a Bachelor of Science degree with a major in Data Science students must complete a minimum of 128 credits and meet the following requirements:

General Education Requirements

In order to graduate on-schedule without taking additional courses, it is highly recommended that students meet with an Undergraduate Academic Adviser concerning the selection of all of their general education courses.

Each candidate for an Oakland University baccalaureate will need to satisfactorily complete approved courses in each of the following areas: Foundations, Explorations, and Integration. For details, refer to the General Education Requirements section of the catalog. In order to satisfy both general education and other program requirements, in some of the general education areas students should select from the courses listed below.

Foundations

• Writing Foundations (WRT 1060)
• Formal Reasoning (Satisfied by MTH 1554; see Mathematics and Statistics)

Explorations: One course from each of the seven areas

• Arts
• Language and Culture
• Global Perspective - ECN 2020 will satisfy the Global Perspective General Education requirement and act as a prerequisite for students pursuing the Economics Application Area.
• Literature
• Natural Science and Technology (Satisfied by Approved Science Elective) - BIO 1200 will satisfy the Natural Science and Technology General Education requirement and act as a prerequisite for students pursuing the Genomics Application Area.
• Social Science - PS 1100 will satisfy the Social Science General Education requirement and act as a prerequisite for students pursuing the Politics Application Area. ECN 2010 will satisfy the Social Science General Education requirement and act as a prerequisite for students pursuing the Economics or Risk Management Application Areas.
• Western Civilization (Satisfied by PHL 1310; see Additional Major Requirements)

Integration

• Knowledge Applications (satisfied by MTH 1555; see Mathematics and Statistics)

U.S. Diversity

• May be met by an approved course in the Explorations area

Capstone and Writing Intensive

• Capstone (satisfied by CSI 4990; see Required Professional Subjects)
• Writing Intensive in the Major (satisfied by CSI 4990; see Required Professional Subjects)
• Writing Intensive in General Education (may be met by an approved course in the Explorations area)

Additional Major Requirements

All Data Science students must complete the following requirement. The course also satisfies the Western Civilization General Education requirement.
• Professional Ethics: PHL 1310 - Introduction to Ethics in Science and Engineering

Mathematics and Statistics

Approved Science Elective

Take one of the following: BIO 1200, BIO 1300, BIO 3000, (CHM 1440 and CHM 1470), CHM 3000, ENV 3080, HS 2000, LIN 1182, PHY 1060, PHY 1200, or (PHY 1510 and PHY 1100).

Data Science Core

Required Professional Subjects

Professional Elective Courses

Students must complete three professional elective courses. At least two of them must be from Group A. Any remaining course can be from either Group A or Group B.

Group A

Group B

Any CSI or STA designated course numbered 3000 or higher

Application Area Courses

Students are required to take two courses from an area in which knowledge of Data Science can be applied, and the application area courses should be completed before taking CSI 4990 (Data Science Capstone). At most one of the courses used to satisfy the application area requirement may also be used to meet the general education requirement. The application area courses need not to be from a single rubric or department but together they should provide a context for Data Science activities. A list of application area courses is provided below. If students are interested in selecting the application area courses from outside the provided list, they are advised to work with a faculty adviser from the Department of Computer Science and to get the application area courses approved before taking such courses. General Elective credits may be needed to meet the 128 credits required depending on chosen Application Area.

Advertising
1. PR 2400 - Introduction to Advertising (4)
2. One of:

Cybercrime
1. CRJ 1100 - Introduction to Criminal Justice (4)
2. CRJ 3341 - Cybercrime (4)

Economics
1. ECN 3020 - Intermediate Macroeconomics (3)
2. One of:

Prerequisites for the Economics Application Area: ECN 2010 and ECN 2020

Environment
1. One of:

2. ENV 4520 - Geographic Information System Analysis for Sustainability (4)

Genomics
1. BIO 3400 - Genetics (4)
2. One of:

Prerequisite for the Genomics Application Area: BIO 1200

Health
1. HS 2000 - Introduction to Health and Health Behaviors (3)
2. One of:

HS 3430 - Sociology of Health and Medicine (4)
PH 3000 - Introduction to Public Health (3)
WHP 3500 - Health Program Implementation (4)
WHP 4850 - Population Health, Health Policy, and Healthcare Delivery (4)

Malware Detection
1. CSI 2470 - Introduction to Computer Networks (4)
2. One of:

Politics
1. Two of:

Prerequisite for the Politics Application Area: PS 1100 .

Risk Management
1. ECN 3500 - Insurance and Risk Management (3)
2. One of:

Prerequisite for the Risk Management Application Area: ECN 2010 .

Supply Chain Management
1. Two of:

Data Science and Computer Science Double Major

Students interested in pursuing a double major in Data Science and Computer Science are encouraged to consult with an academic adviser for a nine-semester course plan.

Major Standing

To enroll in 3000- or higher level courses and to become candidates for the degree of Bachelor of Science with a major in Data Science, students must gain major standing. An application for major standing should be submitted prior to intended enrollment in 3000- or higher level courses. Students can obtain the major standing form from the SECS Undergraduate Advising Website. When the application for major standing is approved, students with majors of Pre-Data Science will have their major changed to Data Science. Approval of both a major standing application and change of major to Data Science is required prior to enrolling in any 3000- or higher-level courses.

To gain major standing in Data Science, students must:

A) have an average GPA of 2.0 in the following mathematics and statistics courses: MTH 1554 , MTH 1555 , and STA 2226 .

B) have an average GPA of 2.0 in the following Data Science core courses: CSI 1320 , CSI 2300 , CSI 2310 , CSI 2810 , and CSI 2999 .

C) have no more than two grades below C in the required courses in A and B above.

D) have not attempted any course listed in A and B above more than three times.

E) have not repeated more than three different courses listed in A and B. Courses in which a W (withdrawal) grade is recorded will not be counted.

Conditional major standing may be granted in the semester in which the student will complete the courses listed in A and B above.

Students who have questions about petition of exception, transfer credit, academic standing, major standing, or any other aspects of their degree programs should consult an academic adviser and other relevant sections of the undergraduate catalog.

Performance Requirements

Satisfactory completion of the program requires an average grade of at least 2.0 within each group: mathematics and statistics, and approved science elective; Data Science core; professional courses which includes required professional subjects, professional electives, and application area courses. Within the professional courses at most two different courses may be repeated, a total of three attempts per course is permitted, and at most two grades below C are permitted. A grade of C or better in CSI 4990 (Data Science Capstone) must be received.

Sample Data Science Schedule

Students entering the School of Engineering and Computer Science with the required background may follow a schedule such as the one indicated below. However, students will need additional time to complete the program if they do not have the required background upon entrance to the program.