Bachelor of Science - Data Science - Statistical Data Science

The Departments of Mathematics and Computer Science have collaboratively developed a new Data Science degree at CWU. This degree will combine both Math and Computer Science courses that focus on producing graduates with the skills needed to query, analyze, and model large data sets. Graduates with a degree in Data Science will be prepared to mine and analyze large, complex, structured and unstructured data sets to uncover hidden solutions to business and technology challenges. A degree program such as this teaches students how to bridge the gap between technology and business interests by using analytics to make informed decisions through foundational training in the principles of statistical and mathematical analysis. In computer science, students will learn the fundamentals of programming, data structures, algorithm design, database design, machine learning and data mining.

Demand for Data Analysts and Scientists remains high nationwide. The competition within industries for market share continues to drive the need for highly technical and analytical employees that can process often massive amounts of raw data in order to pinpoint untapped areas of growth, drive informed and strategic decision making, and identify inefficiencies within an organization. Because of the relatively few undergraduate degree programs specializing in Data Science, CWU again finds itself at the forefront of innovation within degree offerings. This new degree option only enhances CWU’s overall commitment to STEM programs and can be seen as a positive response to the needs of this industry. The focus is on producing data scientists who require strong backgrounds in mathematics, statistics and computer programming.

Upon successful completion of this program, students will be able to: • • Develop relevant programming skills using different programming languages in Data Science. • Apply relevant math skills in calculus, linear algebra, and statistics. • Develop awareness of privacy, security and ethical issues in data science.