DATAn - Data Science Minor
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Program Description
Effective: Fall 2017, Fall 2022
In recent years, data analysis and visualization, computer simulation, and computer modeling have become increasingly important tools for disciplinary research and inquiry. In many areas the change has been revolutionary, transforming the nature of knowledge itself. For example, without computing technology, we simply could not know what we do today about genomics, neuroscience, or geography. Further from traditional science disciplines, data—supported by tools that access, process, summarize, and visualize it—have given us Google Translate, GPS, instant access to centuries’ worth of music and art, and much more.
Data science has arguably democratized knowledge and information (if sometimes imperfectly). This minor will enable students to participate in the data revolution not only as consumers, but as creators and developers, and to understand and experience the role of data technology in modern research and decision making.
Requisites
Requirements for the Minor (24 credits)
I. Preparatory Courses (8 credits)
Complete the following:
a. One introductory course in computer programming selected from the following list:
course - Introduction to Computer Science in JavaScript
course - Introduction to Computer Science in Python
course - Statistical Computing in R
b. Introductory Statistics
course - Introduction to Statistics
II. Core Courses (8 credits)
Complete 8 credits, selected from the following:
course - Data Science: Introduction, History, and Case Studies
course - Data Visualization
course - Applied Data Analysis
course - Modeling and Simulation OR course - Modeling and Simulation
III. Elective Courses (8 credits)
Complete 8 credits, least 4 credits of which are separate from the four core courses, selected from the following:
course - Information Management
course - Data Visualization
course - Applied Data Analysis
course - Modeling and Simulation OR course Modeling and Simulation
course - Statistics Using R
course - Computational Thinking/Programming in Python
course - Cryptocurrency Investing
course - Sports Statistics
course - Text Mining
course - Applied Regression Analysis
course - Bayesian Statistics
course - Statistical Machine Learning
course - History by the Numbers
course - Geographic Information Systems OR course - Geographic Information Systems
course - Databases & Information Management OR course - Computational Modeling of Neural Systems OR course - Computational Modeling of Neural Systems