The Bachelor of Artificial Intelligence degree provides students the opportunity to gain cutting-edge AI knowledge and skills with a solid theoretical foundation as well as a good understanding of different application areas. This bachelor program prepares students for a productive career in industry, lifelong learning, and for graduate study in AI. The BS in AI is strategically designed to build on the strengths of existing computing programs on campus and produce well-rounded students with a balance between strong theoretical foundations as well as practical and hands-on technical skills. The program also includes a strong professional component for the development of skills in technical communication, ethics, and teamwork. The program was designed to satisfy the local and national industry needs and student learning perspectives.

Program Educational Objectives

• Understand representations, algorithms and techniques used across works in Artificial Intelligence and be able to apply and evaluate them in applications as well as develop their own.
• Understand and apply machine-learning techniques, in particular to draw inferences from data and help automate the development of AI systems and components.
• Understand the various ways and reasons humans are integrated into mixed human-AI environments, whether it is to improve overall integrated system performance, improve AI performance or influence human performance and learning.
• Understand the ethical concerns in developing responsible AI technologies.
• Implement AI systems, model human behavior, and evaluate their performance.

Requirements for the Major in Artificial Intelligence, B.S.

To earn the Bachelor of Science degree with a major in Artificial Intelligence 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, Integration, Writing Intensive, and US Diversity. For details, refer to the General Education Requirements section of the catalog.

Foundation

Writing Foundations (course)
Formal Reasoning (Satisfied by course; see Quantitative Foundations)

Explorations

1 course from each of the 7 Explorations Areas

Arts
Language and Culture
Global Perspective
Literature
Natural Science and Technology (Satisfied by an Approved Science Elective)
Social Science
Western Civilization (Satisfied by course; see Additional Major Requirements)

Integration

Knowledge Applications (Satisfied by course; see Quantitative Foundations)

U.S. Diversity

May be met by an approved course in the Explorations Area.

Writing Intensive and Capstone

Capstone (Satisfied by course; see Required Professional Subjects)
Writing Intensive in the Major (Satisfied by course; see Required Professional Subjects)
Writing Intensive in General Education (may be met by an approved course in the Explorations Area)

Additional Major Requirements

All students must complete the following requirement.

Professional Ethics: course Introduction to Ethics in Science and Engineering

Quantitative Foundations

course Discrete Structures with Applications (4)
or course Discrete Mathematics (4)
course Calculus I (4)
course Calculus II (4)
course Computational Linear Algebra (4)
or course Linear Algebra (4)
course Applied Probability and Statistics (4)

Approved Science Elective

Take 1 of the following:

course Biology I (4)
course Biology II (4)
course Biology and Society (4)
course General Chemistry I (4) and course General Chemistry Laboratory I
course Chemistry, Society Health (4)
course Introduction to Environmental Studies (4)
course Introduction to Health and Health Behaviors (3)
course Language and the Brain (4)
course Earth Science/Physical Geography (4)
course The Physics of Everyday Life (4)
course Introductory Physics I (4) and course General Physic Lab I

Artificial Intelligence Core

course Introduction to Python Programming and Unix (4)
course Object-Oriented Computing (4)
course Data Structures (4)
course Introduction to Data Science in Python (4)

Required Professional Subjects

course Software Engineering and Practice (4)
course Security and Privacy in Computing (4)
course Design and Analysis of Algorithms (4)
course Ethics and Bias in AI (4)
course Artificial Intelligence (4)
course Deep Learning and Applications (4)
course AI for IT Operations (4)
course Machine Learning (4)
course Natural Language Processing (4)
course Information Retrieval and Knowledge Discovery (4)
course Senior Capstone Project (4)

Professional Electives

Students must complete 3 courses as part of the professional electives requirements. Courses can be selected from within 1 area if the student has a particular academic interest or any combination of courses listed under different areas.

Cybersecurity Area

course Security and Privacy in Computing (4)
course Software Verification and Testing (4)
course Information Security (4) *
course Information Security Practices (4) *
course Industrial Control Security (4)
course Mobile Security (4) *
course AI for Cybersecurity and Privacy (4)
course Network Security (4) *
course Software Security (4)
course Automotive Security (4)
course Bioinformatics (4)

*Prerequisite requirement: course, which can be taken as a flexible elective.

Data Science Area

course Database Design and Implementation (4)
course Data Visualization (3)
course Contemporary Issues in Data Science (3)
course Database System I (4)
course Big Data Analysis with Cloud Computing (4)
course Data Analytics (4)

Edge AI and Distributed Computing Area

*Prerequisite requirement: course, which can be taken as a flexible elective.

Game Development Area

course User Experience Design (4)
course Game Design (4)
course Game Programming (4)

Human-Centered AI and Robotics Area

course Visual Computing (4)
course AI-Human Interaction (4)
course Supply Chain Modeling and Analysis (4)
course Robotic Systems (4)
course Industrial Automation Systems (4)
course Human Factors Engineering (4) *

*Prerequisite requirement: course, which can be taken as a flexible elective.

Note

course (Special Topics), course (Undergraduate Research), and course (Independent Study) may also count toward fulfilling the professional electives requirement, provided each course is at least 3 credits. General elective credits may be needed to meet the minimum of 128 credits required for the degree, depending on the chosen professional electives courses. Students following this catalog may apply any future courses introduced within the professional electives to meet the professional electives requirement.

Flexible Electives

Students must complete a minimum of 4 additional credits in flexible electives. Flexible elective courses can be chosen from 3000-level or higher courses in CSI, BE, ECE, ISE, ME, APM, MOR, MTH, STA, BIO, CHM, or PHY, or from the approved courses listed below. No more than 2 credits of course (Internship) can be used to fulfill the flexible electives requirement. Additionally, courses at the 5000-level require approval from the instructor.

Approved flexible elective courses*:

course Immersive Python (2)
course Ruby for Web Developers (2)
course Programming in Visual C# for .NET Technology (2)
course Programming in C (2)
course C++ for Programmers (2)
course Introduction to Computer Networks (4)
course Introduction to Data Science in Python (4)
course Introduction to Electrical and Computer Engineering (4)
course Introduction to Differential Equations with Matrix Algebra (4)

*Students can receive credit for either course or course, but not both. Similarly, credit can be received for either course or course, but not both.

Optional Concentrations

The Computer Science and Engineering Department offers optional major-dependent concentrations to any student enrolled in the Bachelor of Science degree in Artificial Intelligence. These concentrations aim to broaden students’ knowledge in specific areas. The concentrations will be noted on the transcript of the students. To earn a concentration as part of the Bachelor of Science degree in Artificial Intelligence, students must fulfill all the requirements of the Bachelor of Science degree in Artificial Intelligence and complete a minimum of 15 credits by selecting specific courses. These selected courses also count towards fulfilling the professional and flexible electives requirements of the Bachelor of Science degree in Artificial Intelligence. Completing a concentration requires minimum 128 credits. Please refer to the individual concentration requirements for more details. Students interested in the concentration should consult an Academic Adviser for guidance on course selection. The following major-dependent concentrations are available to students enrolled in the Bachelor of Science degree in Artificial Intelligence:

• Concentration in Cybersecurity

• Concentration in Data Science

• Concentration in Game Development

Students may pursue more than one concentration, but completing multiple concentrations will necessitate more than the standard 128 credits required for the degree. Each concentration must be completed as part of the degree program. At least 8 credits of courses selected from the above groups for the concentration must be non-duplicative with coursework in the student’s minor, another major, or another concentration. Students interested in the concentration should consult an Academic Adviser for guidance on course selection.

Cybersecurity Concentration

Students are required to take all 3 courses from Group A and 1 course from Group B.

Group A:

course Introduction to Computer Networks (4)
course Information Security (4)
course Information Security Practices (4)

Group B:

course Software Verification and Testing (4)
course Mobile Security (4)
course Network Security (4)
course Software Security (4)

Students can substitute at most 1 course from Group B with at least 3 credits of course (Special Topics), course (Undergraduate Research), or course (Independent Study) provided that the coursework is in the area of Cybersecurity. Approvals of both the instructor and the chair of the Department of Computer Science and Engineering are required for such a substitution.

Data Science Concentration

Students are required to take 4 courses: both from Group A, none or 1 from Group B, and the rest from Group C.

Group A:

course Introduction to Data Science in Python (4)
course Database Design and Implementation (4)

Group B:

course Data Visualization (3)
course Contemporary Issues in Data Science (3)

Group C:

course Database System I (4)
course Big Data Analysis with Cloud Computing (4)

Students can substitute at most 1 course from Group B or Group C with at least 3 credits of course (Special Topics), course (Undergraduate Research), or course (Independent Study) provided that the coursework is in the area of Data Science. Approvals of both the instructor and the chair of the Department of Computer Science and Engineering are required for such a substitution.

Game Development Concentration

Students are required to take all 3 courses from Group A and 1 course from Group B.

Group A:

course User Experience Design (4)
course Game Design (4)
course Game Programming (4)

Group B:

course Web and Mobile Systems (4)
course Android Application Development (4)

Students can substitute at most 1 course from Group B or Group C with at least 3 credits of course (Special Topics), course (Undergraduate Research), or course (Independent Study) provided that the coursework is in the area of Game Development. Approvals of both the instructor and the chair of the Department of Computer Science and Engineering are required for such a substitution.

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 Artificial Intelligence, 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-Artificial Intelligence will have their major changed to Artificial Intelligence. Approval of both a major standing application and change of major to Artificial Intelligence is required prior to enrolling in any 3000- or higher-level courses.

To gain major standing in Artificial Intelligence, students must:

have a minimum average GPA of 2.0 in major standing courses which consist of course, course, course or course, course, course, course, course, and course;
have no more than 2 grades with C-, D+, or D in the major standing courses;
have not attempted any major standing course more than 3 times; and
have not repeated more than 3 different major standing courses, with courses bearing a W (withdrawal) grade not being counted.

Conditional major standing, which permits students to register for 3000- or 4000-level SECS courses, will be granted in the semester during which the student will fulfill requirements for major standing courses.

Performance Requirements

Satisfactory completion of the program requires an average grade of at least 2.0 within each group: quantitative foundations and approved science elective; artificial intelligence core; and professional courses (including required professional subjects, professional electives, and flexible electives). Within the professional courses at most 2 different courses may be repeated, a total of 3 attempts per course is permitted, and at most 2 grades below C are permitted. A grade of C or better in course (Senior Capstone Project) must be received.

Sample Artificial Intelligence 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.

Freshman Year
Fall Semester – 16 credits

course Calculus I (4)
course Introduction to Python Programming and Unix (4)
General Education (4)
General Education (4)

Winter Semester – 16 credits

course Calculus II (4)
course Object-Oriented Computing (4)
course Applied Probability and Statistics (4)
General Education (4)

Sophomore Year
Fall Semester – 16 credits

course Discrete Structures with Applications (4)
or course Discrete Mathematics (4)
course Data Structures (4)
course Introduction to Data Science in Python (4)
General Education (4)

Winter Semester – 16 credits

course Computational Linear Algebra (4)
or course Linear Algebra (4)
Approved Science Elective (4)
General Education (4)
General Education (4)

Junior Year
Fall Semester – 16 credits

course Software Engineering and Practice (4)
course Design and Analysis of Algorithms (4)
course Ethics and Bias in AI (4)
General Education (4)

Winter Semester – 16 credits

course Artificial Intelligence (4)
course Deep Learning and Applications (4)
course AI for IT Operations (4)
Professional Elective (4)

Senior Year
Fall Semester – 16 credits

course Security and Privacy in Computing (4)
course Machine Learning (4)
course Natural Language Processing (4)
Professional Elective (4)

Winter Semester – 16 credits

course Information Retrieval and Knowledge Discovery (4)
course Senior Capstone Project (4)
Flexible Elective (4)
Professional Elective (4)

Applicable Minors

All Minors are applicable to this major with the exception of the following Minor(s): Artificial Intelligence, Child Welfare, Computer Science, and Information Technology.

Artificial Intelligence

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Requirements

Major Dependent Concentration(s)

Major Dependent Concentration Declaration

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