Artificial Intelligence and Machine Learning

The Associate in Science in Artificial Intelligence and Machine Learning provides a rigorous, computer-science-based pathway focused on the design, training, and evaluation of intelligent systems. Students build a strong foundation in calculus, linear algebra, and discrete mathematics; complete CS1-CS2 in either Java or C++; and study computer organization and systems programming. A three-course AI sequence develops probability for computing, supervised and unsupervised learning, search and reasoning under uncertainty, and ethical/responsible AI practices. Hands-on labs and projects emphasize model development and evaluation, software tooling, and deployment considerations such as performance, reliability, and fairness. The degree prepares students for entry-level roles supporting AI initiatives and for transfer to bachelor’s programs in computer science with an AI/ML emphasis.

AS Degree: Projected annual enrollment/completers is 30 students

College of San Mateo’s proposed Associate in Science in Artificial Intelligence and Machine Learning (AI/ML) is designed as a Career Technical Education (CTE) program with a clear transfer to workforce pathway. The degree responds to accelerating regional demand for AI/ML competencies by preparing students to implement, evaluate, and support AI-enabled systems across industries. Students develop rigorous foundations in mathematics and computer science and then apply those foundations in a three-course AI sequence focused on probability for computing, machine learning, and core artificial intelligence methods, with an emphasis on responsible and ethical practice.

Program Learning Outcomes (students will be able to…)

•Apply calculus, linear algebra, and discrete mathematics to reason about algorithms, data, and statistical models used in AI/ML.

•Implement robust software solutions in a modern programming language (Java or C++) and use appropriate data structures to support AI/ML workflows.

•Train, validate, and evaluate supervised and unsupervised learning models using standard metrics and sound experimental methodology.

•Explain and apply foundational AI concepts, including search, reasoning under uncertainty, and problem formulation.

•Recognize and address core responsible-AI considerations such as bias and fairness, privacy, security, transparency, and reliability.

•Communicate technical results effectively in written and oral form and collaborate productively in teams using contemporary tooling.

The degree requires 60 total units: 40 units in the major and 20 units of general education. The major consists of Mathematics (13 units) and core computer science/AI coursework (27 units).

No additional information.

At the time of submission, no colleges in the immediate Mid-Peninsula service region were identified as offering a directly comparable AI/ML associate degree program that would be impacted by this proposal.