Data Science Minor

The objective of this minor is to provide a basic background in data science for those who are more interested in the theoretical underpinnings of analytics and data science.

Students must complete five courses (20 credits) with a cumulative minimum grade point average of 2.0 and with no grade below a C- grade. Transfer course approval for the minor is limited to at most, two relevant courses successfully completed at another accredited institution, subject to syllabi review and approval. Some preparation in MATH 425: Calculus I and programming (CS 415: Introduction to Computer Science I, or COMP 425: Introduction to Programming) is required.

CS 515Data Structures and Introduction to Algorithms4
Select one course from the following:4
From Programs to Computer Science (Durham Students)
Introduction to Computer Science II
Data Structures Fundamentals (Manchester Students)
Select three courses from the following: 112
Introduction to Artificial Intelligence
Machine Learning
Information Retrieval
Mathematical Optimization for Applications
Database Systems
Linear Algebra for Applications
Advanced Statistical Modeling
Data Mining and Predictive Analytics
Applied Regression Analysis
Neural Networks
Mining Massive Datasets
Total Credits20

Must select at least one CS and one MATH course. Must select CS 750: Machine Learning or MATH 738: Data Mining and Predictive Analytics.

For more information, contact Matthew Magnusson, program coordinator and minor supervisor, at