Data Science Minor

Effective: Fall 2017

Requirements for the Minor (24 credits)

Click on the hyperlinked course subject/number to view course details including prerequisites and course attributes. Students should speak with the instructor if they do not meet any prerequisites for the course and wish to register.

I. Preparatory Courses (8 credits)

a. One introductory course in computer programming selected from the following list:
CSCI 149 - Introduction to Computer Science in JavaScript
CSCI 150 - Introduction to Computer Science in Python
STAT 120 - Statistical Computing in R
b. Introductory Statistics
STAT 207 - Introduction to Statistics

II. Core Courses (8 credits)

DATA 200 - Data Science: Introduction, History, and Case Studies
DATA 251 - Data Visualization
DATA 252 - Modeling and Simulation
DATA 253 - Applied Data Analysis

III. Elective Courses (8 credits)

At least 4 credits separate from DATA 251-253

STAT 400 - Statistical Machine Learning
DATA 251 - Data Visualization
DATA 252 - Modeling and Simulation
DATA 253 - Applied Data Analysis
DATA 299 - Data Science Across the Curriculum
HIST 215 - History by the Numbers
ESS 302 - Geographic Information Systems
OR
BIOL 302 - Geographic Information Systems
CSCI 330 - Databases & Information Management
OR
NEUR 366 - Computational Modeling of Neural Systems
OR
PHYS 366 - Computational Modeling of Neural Systems

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Data Science Minor

Requirements for the Minor (24 credits)

I. Preparatory Courses (8 credits)

II. Core Courses (8 credits)

III. Elective Courses (8 credits)