Data Science (Minor)

Data Science (Minor)
Data Science students working

Focusing on the theoretical, mathematical and computational foundations of modern data science, our Data Science minor prepares you with the understanding of how to interpret and manipulate data.

The field of analytics and data science impacts nearly all aspects of the economy, society and daily life. This highly interdisciplinary minor emphasizes mathematics and computer science skills—skills that are in high-demand in industries from finance to healthcare to marketing and more.

What is data science?

With an explosion of big data initiatives in organizations worldwide, the demand for data-savvy individuals has never been higher. This program is designed to provide a basic foundation for students interested in the theoretical underpinnings of analytics and data science. Choose from courses in artificial intelligence, neural networks, data mining and big data. Data science is being applied in many organizations within industry, academy and government, and the job demand reflects this growth. With the experience provided by this minor, you’ll gain a competitive advantage in this rapidly growing field.

Why study data science at UNH?

UNH was one of the first universities in the country to offer an undergraduate-level degree in analytics and data science. Our programs take a multidisciplinary approach that incorporates experiential education and projects. You’ll learn to manage, distill and interpret data for industries from finance to healthcare to marketing and advertising. The data science minor is available at the Durham and Manchester campuses.

Potential careers

  • Actuary
  • Business analyst
  • Consultant
  • Data engineer
  • Data scientist
  • Management analyst
  • Market research analyst
  • Statistician
  • Quantitative analyst

Explore Program Details


Explore Program Details

Curriculum & Requirements

The objective of this minor is to provide a basic background in data science for those who are more interested in the theoretical underpinnings of analytics and data science.
For more information, contact Jeremiah Johnson, minor supervisor.

Students must complete five courses (20 credits) with a cumulative minimum grade point average of 2.0 and with no grade below a C- grade. Transfer course approval for the minor is limited to at most, two relevant courses successfully completed at another accredited institution, subject to syllabi review and approval. Some preparation in MATH 425 Calculus I and programming (COMP 424 Applied Computing 1: Foundations of Programming , CS 414 From Problems to Algorithms to Programs or CS 415 Introduction to Computer Science I) is required.

CS 515Data Structures and Introduction to Algorithms4
Select one of the following:4
COMP 525
Data Structures Fundamentals
CS 416
Introduction to Computer Science II
Select three of the following: 112
CS 730
Introduction to Artificial Intelligence
CS 750
Machine Learning
CS 753
Information Retrieval
CS 775
Database Systems
MATH 645
Linear Algebra for Applications
MATH 736
Advanced Statistical Modeling
MATH 738
Data Mining and Predictive Analytics
MATH 739
Applied Regression Analysis
DATA 750
Neural Networks
DATA #757
Mining Massive Datasets
Total Credits20

Must select at least one CS and one MATH course. Must select CS 750 Machine Learning or MATH 738 Data Mining and Predictive Analytics.