Data Science (BS)

The Bachelor of Science degree in Data Science emphasizes problem-solving in the context of data science and analytics and prepares students for effectively analyzing massive amounts of structured/unstructured data in various application domains. This BS program requires a minimum of 42 credit hours in computer science, about 28 credit hours in mathematics and the sciences, and the university general education program.

The program curriculum provides required data science courses such as introduction to data science, data structures, algorithms, database systems, object-oriented software development, artificial intelligence, information security, and data mining; as well as concentration courses in computer science, statistics, or business.

[ Program Educational Objectives | Student Outcomes | Enrollment and Graduation Figures | Careers | Resources ]

[1] Program Educational Objectives

Graduates of the program are expected to attain the following abilities within a few years of graduation:

  • Grow as well-educated professionals with an integrated high-level understanding of computing systems, processes, and the main body of knowledge of computer science as a whole;
  • Be able to creatively apply theoretical and practical knowledge of computing to develop and support software solutions;
  • Work effectively, as an individual or as a member of a team, while communicating effectively with diverse audiences; contributing to a collaborative and inclusive environment; and complying with the ethical, legal, and professional standards of the discipline; and
  • Maintain their skills as the field evolves and appreciate the need for continuing professional growth and development to keep current in the profession.

[2] Student Outcomes

Students in the program are expected to know and be able to do the following by the time of graduation:

  1. Analyze a complex computing problem and to apply principles of computing and other relevant disciplines to identify solutions;
  2. Design, implement, and evaluate a computing-based solution to meet a given set of computing requirements in the context of the program’s discipline;
  3. Communicate effectively in a variety of professional contexts;
  4. Recognize professional responsibilities and make informed judgments in computing practice based on legal and ethical principles;
  5. Function effectively as a member or leader of a team engaged in activities appropriate to the program’s discipline; and
  6. Apply theory, techniques, and tools throughout the data analysis lifecycle and employ the resulting knowledge to satisfy stakeholders’ needs.

[3] Enrollment and Graduation Figures


[4] Careers

There are numerous careers that require a strong background in Data Science, including data scientist, data architect, data analyst, data engineer, machine learning engineer, machine learning scientist/researcher, business intelligence analyst, business intelligence developer, and business intelligence engineer.

[5] Resources

Requirements for the B.S. degree in Data Science (2021)

Prerequisite chart

Undergraduate Bulletin (Program Requirements)

Undergraduate Bulletin (Course Descriptions): CSCI, MATH, CISA

Academic Maps: Computer Science, Statistics, Business