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Upper-Division Requirements
Competency areas for the Upper-Division Requirements. Hover over each button for course list.


For a full list of course descriptions and requirements, please see the UNC Course Catalog.

Additionally, B.S. in Data Science students complete 18 credit hours for electives over six courses:

  Click for Data Science Electives




Choose four-course concentration and two upper-division electives. Any course listed under the above competencies can be counted as an upper-level elective if it is not counted towards the fulfillment of the competency.

Additional concentrations under development.



DATA 110. Introduction to Data Science. 3 Credits.
This course is a broad, high-level survey of the major aspects of data science including ethics, best practices in communication (e.g. data visualization), mathematical/statistical concepts, and computational thinking. Students will gain an understanding of the fundamentals of data science to support more in-depth, advanced coursework that are requirements for the data science majors. Grading Status: Letter grade.

DATA 120. Ethics of Data Science and Artificial Intelligence. 3 Credits.
In an era of rapid advancements in data science and AI, ethical concerns related to data-intensive technologies are now of utmost importance. This course immerses students in data science ethics, facilitating a comprehensive exploration of the intricate interplay between data and societal values. By nurturing critical thinking grounded in ethical theories, this course provides students with a strong foundation in designing and analyzing data-intensive ecosystems that emphasize values such as fairness, accountability, ethics, and transparency. Grading Status: Letter grade.

DATA 130. Data Literacy Foundations. 3 Credits.
How do you become data literate? Data literacy is the ability to read, write, and communicate data in context, or in other words: perform data analysis, construct a data visualization, and then communicate that data. It is the story that gets told with the data. Data literacy helps us to understand data, learn about different types and scales of data, and understand why this is important in the world today. Grading Status: Letter grade.

DATA 140. Introduction to Data Structures and Management. 3 Credits.
Data structures provide a means to manage large amounts of data for use in our databases and indexing services. A data structure is a specialized format for organizing, processing, retrieving and storing data. There are several basic and advanced types of data structures, all designed to arrange data to suit a specific purpose. Data structures make it easy for users to access and work with the data they need in appropriate ways. Grading Status: Letter grade.

DATA 150. Communication for Data Scientists. 3 Credits.
The ability to collect and analyze data has changed virtually every field, yet data scientists often lack the ability to present their findings in effective formats. This class uses storytelling to help you connect with your audience and present your data in compelling and understandable ways so stakeholders can make the right decisions with data. Through hands-on exercises, you’ll learn the advantages and disadvantages of oral, visual, and written formats. Grading Status: Letter grade.