Matthew Magnusson
Analytics & Data Science Program Coordinator
LECTURER
Data Science (Minor)
Data Science (Minor)
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 on both the Durham and Manchester campuses.
Potential Careers
- Actuary
- Business analyst
- Consultant
- Data engineer
- Data scientist
- Management analyst
- Market research analyst
- Statistician
- Quantitative analyst
Contact
Kingsbury Hall N229, 33 Academic Way
Durham, NH 03824
Phone: (603) 862.3778
E: office@cs.unh.edu
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 Matthew Magnusson, program coordinator and minor supervisor, at matthew.magnusson@unh.edu.
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. and programming (CS 415: Introduction to Computer Science I, or COMP 425: Introduction to Programming) is required.
| Code | Title | Credits |
|---|---|---|
| Requirements | ||
| CS 515 | Data Structures and Introduction to Algorithms | 4 |
| Select one course from the following: | 4 | |
CS 417 | From Programs to Computer Science (Durham Students) | |
CS 416 | Introduction to Computer Science II | |
COMP 525 | Data Structures Fundamentals (Manchester Students) | |
| Select three courses from the following: 1 | 12 | |
CS 730 | Introduction to Artificial Intelligence | |
CS 750 | Machine Learning | |
CS 753 | Information Retrieval | |
CS 757 | Mathematical Optimization for Applications | |
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 | |
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