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Artificial intelligence is an interdisciplinary minor involving a number of academic areas: computer science, mathematics, data analytics, and philosophy. The minor prepares students to work with a powerful, quickly evolving, and controversial tool, in a world that stands to be changed by this tool in ways still only beginning to be understood. Students in the minor will understand the difference between traditional/rule-based approaches to artificial intelligence and more current approaches (such as generative artificial intelligence, which uses massively large data sets to train a system to predictively generate statements, computer code, images, music, and other items). Students will become more proficient at using artificial intelligence. Central to the minor will be the questions of the core curriculum, especially “How should we live together” and “How can we understand the world.”
Requirements for Artificial Intelligence Minor
A minor in artificial intelligence consists of 24 credits, with at least 17 credits in required courses. Required courses are as follows:
- STAT-141
- STAT-142
- CS-357
- DATA-201
- PHIL/CS-243
In addition, artificial intelligence minors must complete 7–8 elective credits to reach 24 credits in the minor. The following courses will satisfy the elective requirement:
- ART-110
- CS-173, 372, 377, 477
- DATA-150, 202, 301, 350
- DIGS-200
- MATH-341
- PHIL-274
- STAT-242, 243, 244, 342, 443W
- Another course, with approval of the artificial intelligence coordinator, that allows for a substantive project involving artificial intelligence.
- Honors or research or an independent study in any discipline that involves significant work with artificial intelligence may also count towards the minor, with the permission of the artificial intelligence coordinator. Students will present their rationale, approach, and socio-ethical considerations via a disseminable project through CoSA, CS/MATH/STAT-350, or other approved means.
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CS-357. Foundations of Artificial Intelligence
A technical introduction to the tools and practices that have evolved from artificial intelligence (AI) and large language models that considers the role of technology through the lens of the Ursinus Questions. This course prepares students to create and interact with conversational virtual assistants and multi-agent systems that achieve goal-oriented outcomes. Students will explore the foundations and history of artificial intelligence that enabled the technical underpinnings of generative AI, with a particular emphasis on the ethical, social, and intellectual property implications of the nature of the training data sets used to form large language models. The course includes a practical discussion of responsible AI from the perspective of creators and of consumers and stakeholders. Students will apply current design patterns in AI with respect to large language models to create and present a technical project using generative AI, and will lead a discussion focused on practices for responsible AI within the context of their chosen project. Offered in Spring of odd years. Prerequisites: CS-170 or CS-173 or DATA-201, or permission from the instructor. Four hours per week. Four semester hours.