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 414: From Problems to Algorithms to Programs, CS 415: Introduction to Computer Science I, or COMP 425: Introduction to Programming) is required.
|CS 515||Data Structures and Introduction to Algorithms||4|
|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: 1||12|
|Introduction to Artificial Intelligence|
|Linear Algebra for Applications|
|Advanced Statistical Methods for Research|
|Data Mining and Predictive Analytics|
|Applied Regression Analysis|
For more information, contact Wheeler Ruml, program coordinator and minor supervisor, at firstname.lastname@example.org.