In this class, students will explore how to combine business domain knowledge with the fundamental principles of data science in formulating a data-driven strategy to meet set objectives. The underlying conceptual processes inherent in the industry-standard CRISP-DM model, namely the systematic progression from business understanding to data understanding, preparation, modeling, and deployment are examined. Real-life scenarios that differentiate between supervised and unsupervised methods for data mining and applied predictive modeling will be considered. Key characteristics associated with deployed analytic models such as generalization and overfitting are introduced. Topics related to responsible data science and ethical practice will also be covered to include transparency, explainability, and fairness.
MIS 1500 and MTH 2310
Course Code: MTH 3150
Credit Hours: 3
Level: Upper-Level
Program Placement: Semester VII
Course description sourced verbatim from the official Northwood University 2025–2026 Academic Catalog and program curriculum guide. Northwood reserves the right to revise course content between publications.