Advanced Methods in Data Science

3.00 credits · Undergraduate

Prereq: MATH 1311; 3 credits from DATA 3001, 3101; or permission of the Department This course introduces advanced methods of data curation, data analysis and data visualization. It explores advanced techniques for curating data from unstructured sources, visualization and analysis techniques for unstructured data sources (including, but not limited to word clouds, similarity metrics, leveraging natural language models for quantitative analysis, etc.), and the foundations of Bayesian data analysis. This course will use a variety of programming environments and languages. (Format: Lecture 3 Hours) (Exclusion: Any version of DATA 4001 previously offered with a different title)