Data Analysis I

Catalog description

Data science is about 80% data preparation and 20% modeling. Data Analysis I begins a two-course sequence that explores the better part of the 80%: methods for collecting and extracting data, joining data, aggregating data, cleaning and pre-processing data. Students will learn how to ask questions of the data that they have, how to enrich data, clean data, handle missing values and how to aggregate it so that the data are ready for analysis. Ethical considerations for decisions made in data pre-processing will also be discussed. Use cases for both structured and unstructured data will be explored. Current methodologies for conducting data analysis and data mining will be used.