Machine Learning for Social and Behavioral Research

(3 Credit Hours) · Undergraduate

Machine learning is becoming an important tool in psychology, offering new ways to analyze data, make predictions, and uncover patterns that may be difficult to detect with more traditional methods. This undergraduate course introduces the core ideas behind machine learning and their application to psychological research. Students will learn how prediction-focused methods can complement hypothesis-driven approaches by helping researchers evaluate models, classify outcomes, and explore complex relationships in data. Topics may include regression and classification, cross-validation, regularization, decision trees, random forests, k-nearest neighbors. The course emphasizes hands-on learning, clear interpretation, and thoughtful use of machine learning in psychological and behavioral science.