Data Science Courses and Requirements

The data science minor will provide the necessary background for students to engage with a world which is awash in data across every discipline. Courses in the five core areas give students an understanding of the importance of the computational, statistical, mathematical, and ethical intersection when using data to form conclusions and gain insight.  The capstone project requirement will make the learning objectives real as each student will grapple with the knowledge that can be obtained in their own data driven project.

Every student who goes through the data science minor will have core competencies to be able to:

  • Recognize the social and ethical responsibilities of a professional working in data science.
  • Understand how to design and implement solutions for computational data problems.
  • Have the capacity to work collaboratively in teams to generate computational products.
  • Communicate effectively, both orally and in writing.

The specific learning outcomes broken down by competencies below.

Data Science Minor Goals and Objectives

Statistical / computational / mathematical understanding

  • Students will have proficiency with statistical analysis of data from one or more disciplinary areas using statistical software.
  • Students will understand computational concepts relevant for data science such as computational efficiency and data structures.
  • Students will show proficiency in the probability and theory of statistics and the application of these concepts to data.

Application of computational approaches

  • Students will demonstrate proficiency in applying algorithmic, mathematical, and scientific reasoning to a variety of computational problems in at least one high level programming language appropriate for data science.

Making decisions

  • Students will develop understanding of different ethical philosophies that can be applied to data-driven decisions.
  • Students will learn how to develop and make decisions regarding the analysis of data to assess scientific claims within an ethical framework.


  • Students will be able to communicate the results of data-driven analyses using literate programming clearly and persuasively.
  • Students will have familiarity with common tools of data science such that they will be able to work closely and communicate effectively with decision makers and stakeholders in a variety of fields.

To culminate the program, students will complete a data science capstone which puts into practice the concepts covered in the coursework. The capstone highlights how the technical, analytical, and ethical aspects combine to solve real world problems. Students give oral presentations on their projects. Before enrolling in the capstone class, students must have completed courses from each of the five core areas and have a project lined up outside of statistics, mathematics, and computer science.