MATH 340 Data Mining and Visualization
This course offers an overview of data and text mining techniques, providing students with a solid foundation in various methodologies. Topics covered include logistic regression analyses, classical discriminant analyses, association rule mining, decision tree algorithms, support vector machines, neural networks, variable reduction techniques, cluster analysis, text analytics, and web mining. In addition, this course emphasizes the practical skills needed for effective data visualization, including computer graphics, visual data representation, understanding human vision models, numerical representation of knowledge and concepts, pattern analysis, and computational methods.
PRQ: CSCI 170 and MATH 223 or permission by instructor
Scheduled: Spring, As needed
Meets: NO
Offered
Spring, As needed