CIT-187: Data Analytics & Pred Analy

Data analytics and predictive analysis encompasses a variety of machine learning techniques to analyze and gather insight from data. The data can then be used either to make predictions of future events, or to classify data into different segments. This course is the follow-up course to Introduction to Big Data with R and R-Studio, and will continue to develop a student's skills in the R programming language. It will also continue to grow a student's understanding of data. Students will learn the difference between supervised and unsupervised modeling, and the basic modeling techniques pertaining to each. The techniques taught in the course include regression, clustering, classification and tree-based methods, along with an introduction to neural networks. Prerequisites: Intro to Big Data with R and R-Studio (CIT137) and Statistics I (MAT181).