CPSC 033. Foundations of AI & Machine Learning

This course provides a rigorous introduction to the core mathematical, computational, and data-driven concepts that underlie modern AI systems. Students will learn essential tools from linear algebra, basic statistics, and Python programming while gaining hands-on experience with the full data pipeline, from acquisition and cleaning to modeling and evaluation. Topics include logistic regression, neural networks, dimensionality reduction, data visualization and model assessment techniques.

In parallel with the technical material, the course examines the societal and ethical implications of AI, exploring issues such as data provenance, bias, transparency, and the real-world consequences of automated decision-making. Through a combination of readings, discussion, labs, and a final project, students will develop both the analytical skills and critical perspective needed to engage responsibly with contemporary AI technologies and to succeed in upper-level courses in the field.
Natural Science.
1.0 credit.
Fall 2026. Staff.
Catalog chapter: Computer Science
Department website: https://www.swarthmore.edu/computer-science

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