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OPER 6607 Machine Learning for Business Intelligence (Spring: 3 )

Course Description

Machine learning (ML) has been a popular topic for data scientists and analysts. The goal in ML is to learn from existing data and extract useful information such as patterns, behaviors and trends. We can then use this information to predict future activity. The ability of learning patterns from data and making accurate predictions on new instances makes ML a powerful tool for Business Intelligence since it helps us transform the raw data into better decisions. This course will not dive into the technical details of ML algorithms but rather focus on how to use these algorithms in Business Intelligence applications. We will study business applications including but not limited to customer segmentation, propensity and churn.

Schedule: Periodically

Instructor(s): The Department

Prerequisites: OPER1135. OPER1135, OPER7705, or OPER7725.

Cross listed with:


Last Updated: 24-Jun-17