Data Science

Course Description

Overview of the concept of data mining, machine learning, big data, and data analytics, including the business challenges of working with data to solve real-world business problems. Students become familiar with the Cross Industry Standard Process for Data Mining (CRISP-DM). Fundamental concepts include Business Problem Understanding, Data Understanding, Data Preparation, Modeling, Evaluation, and Deployment. Data analytics in industry verticals are discussed, including science, intelligence and law enforcement, health, retail and financial services.

Prerequisite: Graduate standing.

Schedule Type: Lecture

Contact Hours: 3 lecture

Grade Mode: Standard Letter