Data Science, Minor

The minor in data science studies the collection, manipulation, storage, retrieval, and computational analysis of data in its various forms, including numeric, textual, image, and video data from small to large volumes.

Note: CCIS minors are only available to non-CCIS majors; students in CCIS-only or CCIS-combined degrees are not eligible for CCIS minors.  A student may receive at most one CCIS minor, regardless of how many CCIS minors they qualify for.​

Complete all courses listed below unless otherwise indicated. Also complete any corequisite labs, recitations, clinicals, or tools courses where specified.

Required Courses

Computer Science Fundamental Courses
A grade of C– or higher is required in computer science fundamental courses.
Complete one of the following options:5-10
Fundamentals of Computer Science Option
Fundamentals of Computer Science 1
and Lab for CS 2500
Fundamentals of Computer Science 2
and Lab for CS 2510
Programming with Data Option
Programming with Data
and Practicum for DS 2000
Data Science Required Course
DS 4100Data Collection, Integration, and Analysis4

Data Science Electives 

Complete three of the following. Only one course from the Meaningful Minor list may contribute toward the minor requirements:12
DS 2010 to DS 4989
Database Design
Meaningful Minor list (see below)

CCIS Meaningful Minors

The concept of “CCIS Meaningful Minors” allows students the chance to personalize a computer or information science minor to meet individual academic needs and interests. Students may take one elective related to computation or information from a preapproved list of courses offered across the university rather than from within CCIS. This allows students to integrate the minor with a course in their own major or with a course in another area of interest. Students may of course choose to take all electives in the minor within CCIS if they wish.

Arts, Media and Design
Information Design 1
Information Design 2
Information Design Studio 1: Principles
Information Design History
Research Methods for Design
Visualization Technologies 1
Information Design Studio 2: Dynamic Mapping and Models
Information Design Studio 3: Synthesis
Game Design and Analysis
Data-Driven Player Modeling
Bouvé Health Sciences
Introduction to Health Informatics and Health Information Systems
Data Management in Healthcare
Personal Health Interface Design and Development
Personal Health Technologies: Field Deployment and System Evaluation
D'Amore-McKim—Business
Advanced Financial Strategy
Information Resource Management
Data Management in the Enterprise
Marketing Research
Marketing Analytics
Supply Chain and Operations Management
Computer and Information Science
Foundations of Information Assurance
Security Risk Management and Assessment
Engineering
Advanced Engineering Algorithms
Data Visualization
Introduction to Machine Learning and Pattern Recognition
Computer Vision
Data Mining for Engineering Applications
Science
Bioinformatics Computational Methods 1
Bioinformatics Computational Methods 2
Biostatistics
Linear Algebra
Probability and Statistics
Statistics and Stochastic Processes
Statistics in Psychological Research
Social Science and Humanities
Statistics
Intermediate Selected Topics in Microeconomics
Quantitative Techniques

GPA Requirement

2.000 GPA required in the minor