Data Science at Nebraska

Data Science

Closeup of data output screens and overlay of globe
Data science prepares you with hands-on experience and competency in data analysis, algorithm design and implementation as you develop aptitudes for interdisciplinary problem solving. The program enables you to take advantage of career opportunities in statistical modeling, software design or Big Data solutions.

The Nebraska Difference


Hands-On Learning

Assist distinguished faculty in groundbreaking research.


Develop Career Skills

Apply mathematical and scientific skills to solve real-world problems.


Interdisciplinary Program

Discover practical applications through interdisciplinary contexts and experiences.

Three Pathways For Data Science

You can major in data science in the College of Agricultural Sciences and Natural Resources, College of Arts and Sciences or College of Engineering. Each pathway prepares you for your future career and offers many of the same required courses. When choosing a college, think about your other interests, the general requirements of the college and available scholarships. View the four-year plans or meet with an academic advisor to see which option is best for you.
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Program Features

Silicon Prairie Location 

The university is within walking distance of dozens of local tech startups and thriving companies. Students don’t have to look far to land a great internship or a first job. 

Professional Development 

Take courses specifically geared toward career preparation, including statistical collaboration, writing, presentation and code documentation. Further your development as a collaborator by working with consulting clients in a capstone course. 

Undergraduate Research 

Our students are invited and encouraged to participate in faculty-supervised research supported by grants and the Undergraduate Creative Activities and Research Experience (UCARE) program

Students in lecture hall listening to faculty member

Notable Courses

Computer Science Informatics Focus (CSCE 155T)

Introduction to computer problem solving methods, software development principles, computer programming and computing in society.

Data Analysis (CSCE 320)

Practical experience on how to model data through existing techniques, including object-oriented and relational models.

Technical Skills for Statisticians (STAT 349)

Creation of research reports, business reports and executive summaries, with a focus on real-world applications in research, business and public service.

Advanced Social Network Analysis (SOCI 430)

Theoretical/conceptual ideas at the heart of the network approach, how to interpret network data and how to apply network ideas and methods to social problems.

Computer Science Professional Development (CSCE 486)

Professional practice through familiarity with current tools, resources and technologies. Professional standards, practices and ethics and report styles used specifically in the field of computer science.

Development of Statistical Software (STAT 451)

Advanced statistical software development. Packaging code into functions, intelligent software design, compiled languages to speed up code, development and release cycles.

Huskers Do Big Things


  • Data science intern, Ameritas
  • Data engineering intern, John Deere
  • Software development intern, Sandhills Global
  • UX design intern, Microsoft
  • Software engineering intern, Lockheed Martin
  • Application development intern, Buildertrend


  • Data engineer, Hudl
  • GIS web developer/analyst, The North Jackson Company
  • Statistical analyst, Experian
  • Mobile software engineer, Epic
  • Database developer, Sandhills Global
  • Software engineer, Microsoft

Graduate Schools

  • Ph.D., Economics, University of Tennessee
  • Master's degree, Computer Science, University of Malaya
  • Ph.D., Neural Computation, Center for Neural Basis of Cognition
  • Ph.D. Computer Science or MBA, University of Nebraska–Lincoln
  • M.S. Information Networking, Carnegie Mellon University
  • M.S. Computer Science, University of Southern California

Outside the Classroom

Get the most out of your collegiate experience by taking advantage of opportunities to get involved. Challenge yourself and make meaningful connections along the way.


Academics & Experiential Learning

  • Develop foundational expertise in the mathematical, statistical and computational aspects of data science as well as its application.
  • Add an additional major and at least one focus area in complementary subjects that will enrich your data science studies.

Career Preparedness

  • Foundational knowledge and expertise in the analysis of large-scale data sources from the interdisciplinary perspectives of applied computer science, data modeling, mathematics and statistics.
  • Abilities and professional skills to solve multidisciplinary data science problems as a member of a diverse team.


  • Discover your career pathway through mentorship from faculty or members of industry.
  • Become a Student Ambassador and connect with prospective students and families.

Have Questions? We're Here to Help

If you have questions about the Data Science major or navigating the application process, contact us.

Sue Ellen Pegg portrait
Contact Name
Sue Ellen Pegg
Contact Title
College of Agricultural Sciences and Natural Resources
Nicholas Gordon portrait
Contact Name
Nicholas Gordon
Contact Title
College of Arts and Sciences
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Contact Name
Jeff Beavers
Contact Title
College of Engineering