Online Bachelor of Science in Data Science (BSDS)
Data Science
Program Overview
Students in the Data Science B.S. program learn to transform raw data into meaningful information using data-oriented programming languages through core data mining, statistics, and data modeling skills. Students learn to extract, prepare, and visualize data, which they then model and analyze. Students learn to apply these skills with sector-specific knowledge in the capstone course, where they develop workforce-ready skills on real-world projects.
Why Choose Data Science?
There is a growing need for Data Science professionals that spans across industries. Graduating with a Bachelor’s Degree in Data Science sets you up to succeed in a variety of roles with competitive salaries. You can customize your degree path to fit your personal career goals.
Admission Requirements
- Minimum 2.0 cumulative GPA
- Minimum 1 transfer credit hour (must be earned post-high school graduation)
- Applicants who have earned fewer than 24 credit hours must also submit a high school transcript.
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Featured Courses
Introduction to the essential elements of data science through the examination of data sets drawn from a variety of fields. Explores data collection and management, exploration and visualization of data, modeling, computing, and ethical issues associated with data science. Introduces students to programming through hands-on activities.
Survey of modern algorithms and methods in data science, focusing on how, why, and when various methods work. Includes topics in statistics, machine learning, and optimization.
This course covers the all-important data “wrangling” process, taking data from real-world sources and converting the data into easily-accessible format for analysis. The course covers the steps of the data wrangling process like importing data, tidying data, string processing, HTML parsing, working with dates and times, and text mining. We will consider databases as well as data extracted from documents.
Covers basics of data visualization and exploratory data analysis. This course is project-oriented and focuses on foundational concepts, recent research results, and best practices for combining raw data from a variety of domains with automated analytical methods and interactive visual interfaces to support analytical reasoning.
