Advanced Data Science

Catalog description

Explores key data science areas including question formulation, data collection and cleaning, visualization, statistical inference, predictive modeling, and decision making. Through an emphasis on data-centric computing, quantitative critical thinking, and exploratory analysis this class covers principles and techniques of data science, including languages for transforming, querying and analyzing data; algorithms for machine learning methods including regression, classification and clustering; principles behind creating informative data visualizations; measurement error and prediction; and techniques for scalable data processing.