Data Science and Machine Learning    3 s.h

Catalog description

Basic methodologies for the data science pipeline: data acquisition and cleaning, handling missing data, exploratory data analysis, visualization, feature engineering, modeling, interpretation, and presentation in the context of real-world datasets. Classical models and techniques for classification, clustering, anomaly detection, deep learning, and collaborative filtering. Prereq.: CSIS 3722 with a grade of C or better. Cross-Listed: CSCI 6951 .