Data Science (DATA)

Professors: B.K. D'Ambrosia (Chair), L. Seiter; Associate Professors: S. Fang, E Manilich; Assistant Professor: P. Banerjee; Instructor: D. Duncan.

Major Programs

The Department of Mathematics, Computer Science, and Data Science offers a bachelor of science in Data Science. The department also offers Mathematics (MT) and Computer Science (CS) programs that are described in separate sections.

Data Science is an emerging academic discipline, a response to an increasing demand for people who are able to understand and analyze data. Data science provides powerful approaches for transforming large and complex data into information, knowledge, and intelligent decisions. John Carroll University’s Data Science program utilizes an interdisciplinary approach with a focus on statistics and computer science, applied to a specific discipline such as business intelligence, communications, digital humanities, entrepreneurship, exercise science, biology, physics, political science, psychology, and sociology. The major in Data Science leading to the B.S. prepares students to explore the complex relationships between data, technology, and society. Data is everywhere, so data science skills are increasingly critical in almost every discipline. Data science careers span the spectrum of possibilities from working for national companies with large data analytics departments to founding entrepreneurial start-up companies at the frontier of future technology, while filling critical roles in all fields, including medicine, business, arts and entertainment, sports, government, law, manufacturing, and research.

Minor Programs

The minor in Data Science provides students with a blend of statistics and programming experiences that are fundamental to the further study of data science.

The minor in Statistics & Analytics provides students with a variety of experiences in data analytics and statistics. 

Students may not earn both the minor in Statistics & Analytics and the major in Data Science.

Program Learning Goals for Data Science

  1. Data Acquisition: Students will collect, store, preserve, manage, and share data in a distributed environment through practical, hands-on experience with programming languages and big data tools.
  2. Problem Exploration: Students will develop problem-solving skills through experiences that foster computational and data analytic thinking.
  3. Analysis: Students will develop an in-depth understanding of the key technologies in data science: data mining, machine learning, visualization techniques, predictive modeling, and statistics.
  4. Domain knowledge: Students will experience discipline-specific data use cases in order to solve real-world problems of high complexity.
  5. Interpretation: Students will learn methods for effective data communication and visualization, and demonstrate their use in data representation.
  6. Social Value: Students will explore social and ethical implications of the use of data and technology.