When artificial intelligence became the defining topic in higher education, Taylor University was in no rush to catch up. It was already there.
Taylor’s Computer Science & Engineering Department I’ve been working on AI since the mid-1980s. Faculty have taught courses in introductory AI, expert systems, machine learning, computer vision, and natural language processing for 40 years and across multiple cycles of technology rise and fall. This fall, that long effort will take on a new form. Taylor launches a Bachelor of Science in Artificial Intelligence and Machine Learning. This bachelor’s degree is a specialized major designed to prepare students not only to work with AI, but to lead its development with technical depth, ethical clarity, and a clear Christian understanding of what technology should and should not do.
“AI is not new,” said Dr. Art White, professor emeritus of computer science and engineering who taught at Taylor University for 39 years. “In the mid-1980s, the Computer Science Department experimented with expert systems, and machine learning was first taught at Taylor in the early 1990s. In fact, many of the basic machine learning concepts existed in the 1990s. Eventually, the Internet and the proliferation of GPUs provided the data and computing power and opened the door to doing even more.”
That history is really the point. While other institutions rushed to build academic AI programs in response to the sudden visibility of large-scale language models, Taylor’s program grew out of two years of careful conversations among faculty, board members, donors, alumni, and outside advisors like current CEO Pat Gelsinger. glue and former CEO intel. The result is a program shaped by people who have watched AI evolve over decades, rather than a program assembled to fit the moment.
The new major requires 90 credit hours and builds from a rigorous core in computer science and mathematics to specialized, upper-level work in machine learning, data science, and AI systems. The new course includes a two-semester machine learning sequence with an integrated lab that provides students hands-on time working with complex datasets and building models from scratch. A new Foundational Models and Generative AI course will put students in direct conversation with technologies that are reshaping entire industries. In a two-semester research series, students and supervisors pair up to continually investigate unanswered questions in the field.
based on Christian ethics
Ethics is not an elective subject. That’s a requirement.
It is not attached to the program. Taylor’s approach to AI asks students to address questions beyond code, such as what AI can, cannot, and shouldn’t do, and how it can serve purposes beyond productivity. One of the frameworks that shaped the development of this program was whether AI could be a tool to accelerate the Great Commission: reach more people in more places, with fewer resources, with greater care.
Among other Christian peer institutions, Taylor’s program is the most AI-focused. Taylor’s major devotes much of its required credit hours to coursework in AI and machine learning, and is the only major to require a two-semester research sequence. Built specifically for this program, the required computational linear algebra course addresses the AI training gap among peer institutions by directly integrating the mathematical foundations of machine learning algorithms with computational implementation.
Taylor’s AI-focused depth is competitive against long-term comparisons that include programs from Carnegie Mellon, UC San Diego, Purdue, Penn State, and Illinois Institute of Technology. The Foundation Models and Generative AI course is not required in any of the five secular programs reviewed. The two-semester study sequence coincides in duration with Penn State’s senior design project.
Taylor has focused on AI within the computer science major for many years. This new degree is the next step. An independent major with increased rigor, additional coursework, and more defined preparation for students heading toward AI research, software development, data science, or graduate study in the field.
“Anyone can learn how to use AI tools, and we are preparing students to build the next tool,” said Dr. Fola Ayano, assistant professor of computer science. “Our curriculum takes you beneath the surface to learn the mathematics, architecture, and algorithmic design that power modern AI, so students graduate with a deep understanding of how these systems are not only applied, but also built. They will equip Taylor with the skills to build intelligent systems from the ground up and the ethical foundation to build them responsibly.”
