Data Science Minor

The Data Science minor introduces liberal arts and science majors to a rapidly growing field and equips them with marketable problem solving skills and strategies needed to confront diverse analytic challenges.

The curriculum of the minor is firmly rooted in interdisciplinary education and covers conceptual, computational, and quantitative methods used to distill valuable patterns from the abundance of data that surrounds us. Through coursework, hands-on training, and experiential learning, students will become aware of the challenges and opportunities inherent in successful data analysis. In addition, students will learn the central role that well crafted narrative plays in real-world data science and the ethical conundrums that often attend acquisition and processing of information and application of insights, once gained.

Resume-building skills garnered through completion of this minor are marketable in diverse fields including but not limited to engineering, computer science, medicine, natural and social science, professional and amateur sports, public health and welfare, and race, ethnic, and gender studies.

Unique Requirements: Complete all three categories
Foundational Mathematical Skills: Select one course3-5
FINITE MATHEMATICS FOR BUSINESS AND SOCIAL SCIENCES (GM)
PRECALCULUS (GM) (or waiver)
Foundational Statistical Skills: Select one course3-4
BIOSTATISTICS
BUSINESS STATISTICS
INTRODUCTION TO STATISTICAL REASONING AND ANALYSIS (GM)
APPLIED STATISTICS
BASIC STATISTICAL METHODS
BASIC SOCIAL STATISTICS
STATISTICS FOR SOCIAL WORK
Experiential Learning
Any internship (493), undergraduate research (498R), or similar experience involving quantitative data analysis. Must be approved by the minor coordinator. May also be applied to another major or minor.
Minor Requirements
COMPSCI 170INTRODUCTION TO PYTHON PROGRAMMING (GM)3
COMPSCI 180DATA SCIENCE FOR EVERYONE (GM)3
COMPSCI 181INTRODUCTION TO DATABASE AND THE WEB (GM)3
COMPSCI 310INTERMEDIATE DATA SCIENCE (Intermediate Data Science)3
Ethical and Legal Context: Select one course3
BUSINESS ETHICS (GI)
TECHNOLOGY AND SOCIAL RESPONSIBILITY (GH)
CONTEMPORARY MORAL ISSUES (GH)
THE CONSTITUTION AND CIVIL RIGHTS
Communication Proficiency: Select one course3
PUBLIC SPEAKING (GH)
COMMUNICATION AND TEAM BUILDING (GH)
PERSUASION
WRITING FOR THE WEB
STYLE: PRINCIPLES AND PRACTICES
WRITING IN THE SCIENCES
TECHNICAL AND SCIENTIFIC WRITING
Data Science Electives: Select one course from one group3-5
A. Applications of Data Science Methods to Specific Fields
INTRODUCTION TO EPIDEMIOLOGY (GM)
INTRODUCTION TO EPIDEMIOLOGY (GM)
BIOINFORMATICS
BIOINFORMATICS
GIS I: INTRODUCTION TO GIS AND MAPPING
ECONOMIC GEOGRAPHY
GIS II: SPATIAL DATA AND ANALYSIS
VISUALIZATION, INFOGRAPHICS, AND TECHNICAL DOCUMENTATION
PUBLIC POLICY ANALYSIS AND ADVOCACY
SCIENCE POLICY AND HUMAN HEALTH
US ENVIRONMENTAL POLITICS AND POLICY
ADVANCED AND MULTIVARIATE DATA ANALYSIS FOR THE LIFE SCIENCES
ADVANCED AND MULTIVARIATE DATA ANALYSIS FOR THE LIFE SCIENCES
METHODS OF SOCIAL RESEARCH
B. Additional Analytic Preparation for Select Graduate Programs
INTRODUCTION TO ARTIFICIAL INTELLIGENCE
DATABASE MANAGEMENT SYSTEMS
APPLIED CALCULUS SURVEY FOR BUSINESS AND SOCIAL SCIENCES (GM)
CALCULUS AND ANALYTIC GEOMETRY I (GM)
MATRICES AND LINEAR ALGEBRA
LOGIC (GH)
At least 6 total units must be earned in courses numbered 300 or higher (including COMPSCI 310)
Total Units21-23