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Updated 2025-2026 Undergraduate Catalog | 20265

PDF of Data Science, B.S.

Mathematics

Programs

Data Science, B.S. major


Data science is an interdisciplinary field of scientific methods, processes, algorithms and systems that use data to draw conclusions and make predictions. The data science major provides a strong foundation in statistics and computer science, along with courses in applied areas of study. Students will learn the statistical, computational, and programing tools necessary to prepare them for employment in many applied fields that rely on data. In addition to the overall graduation requirements, the B.S. Data Science major requires each student complete 59 credits in the major with an overall minimum GPA of 2.25. All prerequisite and required courses must be completed with grades of C- or above. This major offers courses in statistics, mathematics, computer science and applied areas. 

A total of 120 semester credits are needed for the Data Science B.S. degree and include the following:

  • 40 upper division credits (level 3000/4000)
  • 55 required major core credits 
  • Completion of Core Curriculum credits (Minnesota Transfer Curriculum [MnTC] Goal Areas 1-10) - required for all baccalaureate degrees
  • Completion of BSU Focus and Nisidotaading Course Requirements

Required Credits: 55
Required GPA: 2.25

I REQUIRED MATH COURSES

Complete the following courses:

II REQUIRED STATISTICS COURSES

Complete the following courses:

III REQUIRED COMPUTER SCIENCE COURSES

Complete the following courses:

IV OTHER REQUIRED COURSES

Select two of the following courses:

 

Program Learning Outcomes | Data Science, B.S.

1. Knowledge: Students will understand the content and methods of the core areas of undergraduate statistics.

2. Analysis: Students will use data and data visualization to identify, interpret and analyze problems, find patterns in data and make conjectures. 

3. Application: Students will apply appropriate statistics and computer science procedures and technology to solve problems.

4. Articulate how biases, both unintended and intended, in data collection techniques, mining algorithms, and analyses can skew the information derived from the data and the effect this can have on diverse groups

5. Communication: Students will communicate results effectively and accurately, both verbally, in writing, and through data visualization. 

6. Career Readiness: Students will be prepared for a variety of careers in industry and further study in data science. 

 

Suggested Semester Schedule | Data Science, B.S.

The following is a list of required Data Science Major, B.S. courses by year. This schedule is intended to help students plan their courses in an orderly fashion; however, these are only suggestions and this schedule is flexible.

Freshman

Sophomore

Junior/Senior