Bachelor of Science in Data Science

Help companies give meaning to their data by earning a data science degree

The need for data scientists is expected to increase drastically over the next 10 years, and graduates of the Marian University Bachelor of Science in Data Science program leave school equipped to address the data analytic and data management needs of organizations.

Students in the BS in Data Science program are prepared to enter the workforce, having honed their abilities to collect, manage, analyze, and interpret data and communicate their results effectively. To prepare learners for a wide range of employment opportunities, we offer extensive preparation in scientific methods, programming, database management, statistics, business decision making, and ethics.

Graduates can work in a wide variety of business sectors that place emphasis on hiring individuals who can investigate the principles of data representation, management, statistical modeling, and analysis, and apply these skills to uncover patterns within Big Data. Students of the Bachelor of Science in Data Science program graduate with experience in advanced data management tools, applied statistics, and operations research techniques.

Learn to be a Data Science Expert

What is Data Science?

Data Science identifies patterns within data sets. Once the pattern is identified, you are able to highlight and communicate these patterns to the business or organization in a variety of industries. Or you can specialize in an area of your own interest such as sports analytics, marketing, education, business, etc. To graduate with a degree in Data Science, you will need to complete two capstone projects with a business outside of Marian.

Jobs to Aspire to:

  • Data scientist
  • Business intelligence analyst
  • Database developer
  • Applications architect
  • Database administrator
  • Infrastructure architect
  • Data engineer
  • Enterprise architect
  • Data analytics manager

BS in Data Science Curriculum

Graduates of the Marian University Bachelor of Science in Data Science program develop a broad background in applied statistics, coding, and research methods and learn advanced quantitative management techniques. With an emphasis on interdisciplinary and applied learning, students will complete two hands-on internships in areas such as sports analytics, finance, manufacturing/operations research, decision science, or data engineering.

Academic Bulletin
SAMPLE COURSE PLAN
FACULTY DIRECTORY

General Education Courses

As a bachelor’s level student, you are required to take about 30 credits of general education courses as part of the 120 credits required for a bachelor’s degree. Gen eds are required regardless of your major.

All students take 10.5 to 17 credits in these areas:

  • Mathematical Reasoning
  • Argumentative and Research Writing
  • Introduction to Christian Theology
  • Interpersonal Communication
  • Introduction to Ethical Reasoning
  • First Year Studies

Core Courses

Data science majors will take courses covering topics such as:

  • Database Management
  • Research Methods
  • Applied Statistics for Social Science
  • Programming and Data Structures
  • Data analytics and Data Mining

Learning Outcomes

Students entering the Marian University Bachelor of Science in Data Science program will master:

  • Data research and ethics: Combine research design and data from more than one perspective; develop a methodology; and discuss relevant solutions, the associated limitations, and implications.
  • Critical thinking and problem solving: Analyze assumptions/viewpoints to carefully place evidence and perspectives to evaluate and articulate limitations.
  • Integrated communication: Organize and synthesize information by choosing formats in verbal, written, and visual language.
  • Technological dexterity: Execute procedures for accurate, reliable, and valid data collection, storage, security, transfer, and export.
  • Quantitative Reasoning: Understand and articulate the mathematical and statistical assumptions and potential consequences related to information, data, and analyses.