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Data Science-Liberal Arts (DATA-LA) Courses

Upper Division

DATA-LA 322 (ANTH 322)(PSYC 322)(SOC 322) PRINCIPLES OF DATA SCIENCE (3-0-3)(F). An introduction to the core concepts of data science including: predictive modeling using machine learning and data mining; data gathering, extraction and cleaning; and exploratory data analysis. Emphasizes practical skills for liberal arts students to examine questions of human behavior using large and complex data sets. May be taken for credit in ANTH, DATA-LA, PSYC, or SOC but not for more than one discipline. PREREQ: Upper-division standing, CS 133, and a statistics course.

DATA-LA 420 (ANTH 420)(PSYC 420)(SOC 420) SOCIAL NETWORK ANALYSIS (3-0-3)(F,S,SU). Introduces and applies concepts and empirical methods of network analysis in a field-based project. Social networks influence learning, economic behavior, and adoption of new products and organizational innovations. May be taken for credit in ANTH, DATA-LA, PSYC, or SOC but not for more than one discipline. PREREQ: Upper-division standing and a statistics course.

DATA-LA 485 (ANTH 485)(PSYC 485)(SOC 485) STATISTICAL MODELING IN R (3-0-3)(S). Focuses on statistical methods for practical data analysis, including parametric and non-parametric analyses, ANOVA, multiple and logistic regression, generalized linear models, and dimension reduction methods using R to examine and understand human behavior. Students will conduct a research project designed in partnership with a professional stakeholder that delivers actionable outcomes. May be taken for credit in ANTH, DATA-LA, PSYC, or SOC but not for more than one discipline. PREREQ: ITM 330 and ITM 340; or DATA-LA 322.