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2026-2027 Undergraduate & Graduate Catalog

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Bachelor of Science in Artificial Intelligence

Major in Artificial Intelligence

Degree Requirements

The Artificial Intelligence (AI) Major at Grand Valley State University is an applied, industry-focused program designed to equip students with practical, hands-on experience and technical expertise, preparing them for high-impact roles in AI-driven sectors. All Artificial Intelligence majors must complete the BS Core Courses (33-37 credits), choose an Emphasis (Emphasis A: 44 credits or Emphasis B: 36-37 credits), and one Elective Track (12 credits).

Artificial Intelligence Majors must complete the following courses. All requirements (sections I, II, III, IV below) must be completed with a minimum 2.0 GPA.

I. BS Core Courses (33-37 credits)
  1. Computing Courses (14-17 credits)
  1. Non-computing Courses (19-20 credits)
II. Required Emphasis: AI majors must choose one emphasis (A or B) below to complete:

A. AI Systems Emphasis (44 credits)

The AI Systems emphasis focuses on programming, algorithms, systems, and advanced AI methods. This prepares students for careers or graduate study in artificial intelligence, machine learning, data science, and software engineering. All students seeking this emphasis complete the following courses:

  1. Required Computing Courses (38 credits)
  1. Required Non-computing Courses (6 credits)

B. Human-Centered Applied AI Emphasis (36-37 credits)

The Human-Centered Applied AI emphasis focuses on the responsible application of AI, human-AI interaction, ethics, visualization, and domain-focused use of AI. This emphasis is designed for students pursuing AI-related roles in healthcare, sustainability, business, policy, education, and other interdisciplinary fields. All students seeking this emphasis complete the following courses:

  1. Required Computing Courses (36-37 credits)
III. BS Elective Courses (12 credits)

AI majors must choose one of the following elective tracks (A-F) (12 credits):

  1. A. AI Deployment and Operations Track

The Artificial Intelligence Deployment and Operations track prepares students to build, deploy, and maintain AI systems with a focus on machine learning operations, generative AI, and reinforcement learning. Students gain essential skills in AI software development, testing, and architecture, preparing them for roles as AI engineers, machine learning operations engineers, and AI software developers.

Required

Choose 9 credits of the following:

(If one of these courses was selected in the requirements above, it cannot be counted again in this track)

Total 12 credits.

  1. B. AI and Cybersecurity Track

The Cybersecurity and Artificial Intelligence track equips students to design, develop, and secure AI systems by integrating core principles of AI trust, security, and ethical hacking. Students gain specialized knowledge in AI security, software assurance, and trustworthy AI, preparing them for roles as AI security analysts, cybersecurity engineers, and ethical hackers in sectors where AI-driven systems must be robust, secure, and ethically sound.

Required

Choose 9 credits of the following:

(If one of these courses was selected in the requirements above, it cannot be counted again in this track)

Total 12 credits.

  1. C. Edge and Cloud AI Track

The Edge and Cloud Artificial Intelligence track prepares students to develop, deploy, and manage AI systems on edge devices and cloud platforms. Students gain skills in hardware-software integration, pervasive computing, and machine learning operations, enabling them to excel as cloud AI engineers, edge AI developers, and system security specialists in industries requiring scalable, low-latency AI solutions.

Required

Choose 6 credits of the following:

Total 12 credits.

  1. D. AI and Business Track

Required:

(If one of these courses was selected in the core above, it cannot be counted again in this AI and Business track)

Choose 9 credits from the following:

Total 12 credits.

  1. E. AI and Healthcare Track

Required:

Choose 9 credits from the following:

Total 12 credits.

  1. F. AI Design Track

A total of twelve credit hours selected by the student from the following list to customize a specialization track that aligns with and complements the student's program goals; selections must be approved by the student's advisor:

Choose 12 credits from the following:

Total 12 credits.

IV. University Degree Requirements 
  • AI majors must also complete the general university degree requirements as identified in the General Academic Regulations section of the catalog. The university B.S. requirements are met through:
Suggested Order of Coursework - AI Systems Emphasis

This suggested order of coursework assumes that students will seek the help of their advisor to complete the courses in a timely manner. The following course sequence also assumes a strong mathematics background for the entering student. If mathematics deficiencies exist, completing the mathematics prerequisites should be the student's top priority.

Year One

Year Two

Year Three

Year Four

Suggested Order of Coursework - Human-Centered Applied AI Emphasis

This suggested order of coursework assumes that students will seek the help of their advisor to complete the courses in a timely manner. The following course sequence also assumes a strong mathematics background for the entering student. If mathematics deficiencies exist, completing the mathematics prerequisites should be the student's top priority.

Year One

Year Two

Year Three

Year Four

Second BS Degree in AI (minimum of 30 credits)

The Second Bachelor's Degree in Artificial Intelligence is a post-baccalaureate pathway designed for individuals who already hold a bachelor's degree and wish to reskill or transition into AI-related fields, building on their prior academic experience to enter or advance in the field of AI.

As artificial intelligence continues to transform every sector, from healthcare and business to education and beyond, there is a growing need for professionals who can apply AI effectively within their domains. Working professionals and career changers will find this program a flexible pathway to reskill and remain competitive in an AI-driven workforce. The curriculum is intentionally interdisciplinary, reflecting the expanding role of AI across diverse fields and real-world contexts, and preparing graduates to leverage AI as a tool for innovation, decision-making, and societal impact.

The Second Bachelor's Degree in AI recognizes the knowledge and skills acquired in the first degree, allowing students to leverage existing foundations while focusing on an AI-specific emphasis in AI Systems or Human-Centered Applied AI. In accordance with GVSU's Credit for Prior Learning policy, students may request an evaluation of prior academic, professional, or experiential learning for potential credit. All requests are reviewed individually, and credit is granted only when prior learning demonstrates clear and direct equivalence to the intended course outcomes.

Admissions Requirements

  • Acceptance into Grand Valley State University as a degree-seeking undergraduate student.
  • The applicant's first bachelor's degree must be earned and officially verified by the university.
  • Overall GPA: Applicants must earn a minimum overall GPA of 2.0 for admission consideration. This overall GPA includes grades in all college-level courses (graduate and undergraduate).

The Second Bachelor's Degree in AI majors must complete one Emphasis area with a minimum of 30 semester hours (assuming all prerequisites as listed are satisfied through prior learning) as follows:

Second BS Degree in AI Based on the AI Systems Emphasis

Prerequisites Courses (32-37 credits)

The following courses are satisfied either through prior learning, such as coursework completed in the student's first bachelor's degree, or by completing the required prerequisite courses before enrolling in advanced courses.

Required Computing Courses (30 credits)

Second BS Degree in AI Based on the Human-Centered Applied AI Emphasis

Prerequisites Courses (30-36 credits)

The following courses are satisfied either through prior learning, such as coursework completed in the student's first bachelor's degree, or by completing the required prerequisite courses before enrolling in advanced courses.

Required Computing Courses (30 credits)


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