MAT 486 - Introduction to Big Data Analytics

This is an introductory course of big data and predictive analytics covering foundational techniques and tools required for data science. The course focuses on concepts, principles, and techniques applicable to industry and establishes a baseline that can be enhanced by further formal training and additional real-world experience. Topics include basic database management systems, data pre-processing, association rules, decision trees, naive Bayes, clustering, and memory-based reasoning. The class follows a learning-by-doing approach in which the students will complete projects on real-world data sets.

Prerequisite(s): MAT 282 or permission of instructor.
Co-requisite(s):
Credits: 3

Course Typically Offered:
Course Type: Mathematics