DSC610 Data Science and its Applications

[3–0, 3 cr.]

This course covers essential data science and the data processing pipeline including data capture (scraping, cleaning, wrangling, and filtering), feature engineering (representation, selection, and transformation), data augmentation, data mining (predictive modeling), data visualization (search and exploration), and scalable computing and big data (Hadoop, Hive, and Spark).  The course concludes with an introduction to supervised learning.

Pre-requisite: DSC602 Python for Data Science and DSC604 Statistics for Data Science