About Our Data Science Minor
The Data Science Minor introduces students to the end-to-end process of investigating data through a machine learning lens. This interdisciplinary program combines mathematical foundations with computational techniques to extract meaningful insights from complex datasets.
Students learn data preparation, visualization methods, and commonly used data analysis techniques. The program emphasizes practical application of statistical and machine learning concepts to solve real-world problems across diverse industries and research domains.
Data Analysis & Visualization
Master techniques for exploring, analyzing, and visualizing complex datasets to uncover patterns and insights
Machine Learning
Learn the full machine learning pipeline from feature extraction to model evaluation and performance assessment
Data Management
Develop skills in data preparation, database systems, and statistical computing essential for data science projects
Why Study Data Science?
Data Science is one of the fastest-growing fields with applications across every industry. Our minor provides students from any major with analytical and computational skills to harness the power of data for decision-making and discovery.
Data Analysis Roles
- Data Scientist
- Data Analyst
- Business Intelligence Analyst
- Market Research Analyst
- Operations Research Analyst
- Statistical Analyst
Machine Learning & AI
- Machine Learning Engineer
- AI Research Scientist
- Deep Learning Specialist
- Computer Vision Engineer
- Natural Language Processing Engineer
- Predictive Analytics Specialist
Technical & Research Roles
- Data Engineer
- Database Administrator
- Research Scientist
- Quantitative Researcher
- Data Visualization Specialist
- Product Data Analyst
Course Requirements
The Data Science minor is open to all students who fulfill the requirements listed below. This program introduces students to the full data science pipeline from data collection and preparation through analysis and interpretation.
Students complete foundational courses in programming, database systems, probability theory, and biostatistics, plus advanced coursework in machine learning or data analysis and visualization.
Data Science Minor Requirements
The Data Science minor is open to all students who fulfill the requirements listed below.
Required Courses (18 Credit Hours)
This is an introductory programming course that emphasizes program specification and design, algorithm development, coding, and testing. Topics include fundamentals of algorithms, flowcharts, problem solving, control structures, data validation, arrays, strings, error handling, and file I/O.
CREDIT: 3 SEMESTER HOUR(S)
Explores database architecture analysis and manipulation with a focus on the relational model. Introduces SQL and entity-relationship models. Students gain practical experience through group or individual projects. Offered every spring.
CREDIT: 3 SEMESTER HOUR(S)
Prerequisite(s): CSC 341
Explores probability, distributions, random variables, expectations, moment generating functions, and the Central Limit Theorem. Offered every fall.
CREDIT: 3 SEMESTER HOUR(S)
Prerequisite(s): MAT 222 with a grade of “C.”
Applies statistical concepts to biological sciences. Topics include data analysis, confidence intervals, significance, and applications in epidemiology and clinical practice. Offered every spring.
CREDIT: 3 SEMESTER HOUR(S)
Prerequisite(s): MAT 103 with a grade of “C.”
Introduces students to investigating data using machine learning. Covers feature extraction, core algorithms, and evaluation of model performance.
CREDIT: 3 SEMESTER HOUR(S)
Prerequisite(s): MAT 222
A project-based course applying mathematics to practical problems. Covers scientific computing, data preparation, visualization techniques, and common analysis methods.
CREDIT: 3 SEMESTER HOUR(S)
Prerequisite(s): MAT 222
Unlock the Power of Data
Join the data revolution and develop skills to extract meaningful insights from complex information. Our Data Science minor provides the analytical foundation to make data-driven decisions in any field.