COMMERCE 3DA3 - Predictive Analytics

3 unit(s)

This course is designed to introduce the basics of predictive analytics to undergraduate students. The course takes a computational approach to address the concept of prediction and forecasting within business problems. Students will learn about the most commonly used predictive analytics tools and methodologies and get to apply them to a series of problems to gain hands-on experience. In this process, students learn the basics of predictive data analytics using state of the art analytics computational platforms and tools. Upon completion of the course, students are expected to have gained a broad understanding of predictive data analytics methods and algorithms (including some machine learning algorithms), and are able to use Python to perform a preliminary predictive analysis on a given data set. The course does not require any prior programming experience.
Lectures (three hours)
Prerequisite(s): COMMERCE 2DA3 (or 3QA3); and registration in any Bachelor of Commerce or Engineering and Management program or relevant minor (see Faculty Note 2.)