Artificial Intelligence

The Department of Computer Science offers a Bachelor of Science in Artificial Intelligence and a minor in Artificial Intelligence at the undergraduate level. This section describes the BS in AI and the AI minor, which provide pathways into the field of AI for students within the major and from other disciplines who wish to bring AI methods to their primary area of study.

The BS in AI is a rigorous four-year program that combines strong mathematical foundations (i.e., calculus, discrete mathematics, linear algebra, and probability) with technical programming skills and specialized AI coursework. Students begin building AI systems in their first year through the redesigned CS 111A/112A/245A sequence and a GenAI and Agents course, then advance through core AI foundations, machine learning, and a suite of electives spanning natural language processing, deep learning, human-centered AI, program synthesis, data engineering, and big data. The program culminates in a team-based capstone project addressing real-world, human-centered needs.

The AI minor offers an accessible pathway for students of any major to develop practical and foundational AI programming skills. It consists of three required foundational courses and two electives from within Computer Science along with departments across the College of Arts and Sciences including: Biology, Mathematics, Physics, Environmental Science, and Philosophy.

Objectives

Provide a comprehensive course of study in the theoretical and practical foundations of artificial intelligence and machine learning, preparing students for graduate study and AI-related careers
Develop a rigorous foundation in mathematics, programming, problem solving, and the algorithms and model structures that underpin modern AI systems
Engage students in hands-on AI system building from their first year, with early exposure to generative AI, agents, and modern development tools
Cultivate critical, interdisciplinary evaluation of AI through coursework in ethics and the broader societal implications of AI design and deployment
Build students’ data engineering capabilities for designing pipelines, databases, and cloud platforms that support scalable AI systems
Develop students’ communication and collaboration skills through group projects, classroom presentations, and a substantial capstone team project addressing human-centered needs
Encourage close interaction between students and faculty through small class sizes and a high degree of availability of professors outside the classroom
Expose students to local researchers and practitioners in AI and computer-related fields
Provide opportunities for undergraduate research with a faculty advisor across the breadth of AI subfields
Enable students pursuing the minor to apply AI methods to their primary field of study through flexible electives across the natural sciences, mathematics, and humanities

Programs

Undergraduate Majors

Artificial Intelligence Major

Undergraduate Minors

Artificial Intelligence Minor