MGMT 433: Predictive Analytics

Businesses are collecting and storing vast amounts of data. Business intelligence (data mining) techniques are used to turn business data into valuable information and generate business intelligence, helping organizations to make effective decisions. This course will provide an understanding of various data mining techniques such as association rules, clustering, classification techniques, etc., and how to use data mining techniques to transform large and complex data into actionable information. The data mining techniques will be examined in business applications such as marketing, e-commerce, finance, and retailing.

Upon completing the course, students will be expected to

a. Write and execute basic commands in R using RStudio.

b. Identify structured, unstructured, and semi-structured data.

c. Implement effective data design with respect to time frame, sampling, and granularity.

d. Identify the types of variables and terminologies used in predictive modeling.

e. Apply the most widely used prediction algorithms and techniques in handling real-world business situations.

f. Examine how predictive analytics can be used in decision-making under alternative scenarios.

g. Translate a vague question into one that can be analyzed with statistics and predictive analytics to solve a business problem.