DataMining & Business Intell.

Catalog description

This course covers fundamental concepts and techniques in data mining with a focus on business application. The goal is to understand how to build and use appropriate data mining models to analyze business-related data and obtain useful information to advance the business and make managerial decisions. The course covers various predictive regression and classification models, such as Multiple Linear Regression, Regularization methods, K-Nearest Neighbors, Naïve Bayes, Logistic Regression, Classification and Regression Trees, Neural Networks, clustering methods, and dimension reduction techniques. Python will be used to implement such models. Hence, proficiency in programming with Python is critical in succeeding in this course. Prerequisites are Python programming, statistics.