Undergraduate

Data Science

Developing an understanding of how to interpret and manipulate data.

Degree

Minor

Location

Manchester, NH

Courses

Credit

20 hrs.

Full-time

- -

Part-time

- -

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UNH MAnchester

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 Data Science Minor emphasizes mathematics and computer science skills—skills that are in high-demand in industries from finance to healthcare to marketing and more

UNH Manchester

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Tuition Costs

Contact Cards

Jeremiah Johnson

Associate Professor

Jeremiah.Johnson@unh.edu

Manchester - 88 Commercial Street, 88 Commercial Street,

(603) 641-4127

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.

Potential careers

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

Curriculum & Requirements

Program Description

Requirements for the Program

Academic policies related to Minors.

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 or CS 415 Introduction to Computer Science I ) is required.

Course List
Code	Title	Credits
Required Courses
CS 515	Data Structures and Introduction to Algorithms	4
Select one course from the following:		4
COMP 525	Data Structures Fundamentals
CS 416	Introduction to Computer Science II
Select three courses from the following: ¹		12
CS 730	Introduction to Artificial Intelligence
CS 750	Machine Learning
CS 753	Information Retrieval and Generation Systems
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 Credits		20