CS 4075 Data Mining and Data Analytics

This course provides a comprehensive coverage of data analytics and its application. Every stage of the CRISP-DM (Cross Industry Standard Process for Data Mining) process, which includes business understanding, data understanding, data preparation, modeling, evaluation, and deployment, will be studied. To make sense of data (i.e., data analytics), data mining and machine learning techniques of association, classification, clustering, and anomaly detection will be covered. Students will also learn the concepts of data warehousing, OLAP (On-Line Analytical Processing), neural networks, as well as deep learning. Ethical and security issues in data science will be introduced. Prerequisite(s): CS 3550 or CS 4400 with at least a C- and MATH 2300 with a minimum grade of C-
Credits: 3.0