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. 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|
|Mathematical Optimization for Applications|
|Linear Algebra for Applications|
|Advanced Statistical Methods for Research|
|Data Mining and Predictive Analytics|
|Applied Regression Analysis|
|Mining Massive Datasets|
For more information, contact Wheeler Ruml, program coordinator and minor supervisor, at firstname.lastname@example.org.