Predictive analytics is the art and science of extracting useful information
from historical data and present data for the purpose of predicting future
trends. In this course, students will have an introduction to the phases of the
analytics lifecycle and a basic understanding of a variety of tools and machine
learning techniques to analyze data to discover forward insights. Several
techniques will be introduced; including data pre-processing techniques, data
clustering algorithms, data classification algorithms, association rules data
mining algorithms, recommender systems, etc.
Applications from bio-informatics, social networks analytics,
and text mining will be covered. Highlights from industrial use cases will be illustrated to demonstrate how Predictive Analytics relates to improving business
performance and impacting better decisions.
This is an introductory course that
will provide students with basic skills of the new generation of data
scientists that will allow them to structure, analyze and derive useful
insights from data that could help make better decisions.