Bachelor of science in data analytics
WSU Bachelor of Science in Data Analytics
A Data-Driven Solution
Data analytics is the application of powerful new methods – drawn from computer science, mathematics and statistics, and domain sciences – to collect, curate, analyze, discover and communicate knowledge from “big data.”
Washington State University is one of only two research universities (and the only one west of the Mississippi) to offer an undergraduate degree specifically designed to prepare students for leadership in data analytics.
Data Analytics tools and techniques are used by many different industries to create, manage, explore and analyze large, complex datasets, in order to evaluate past performance, predict future trends and make better decisions. There has been an explosion of demand for skilled data analysts who can communicate, solve problems and work effectively in teams.
Data analytics preparation
The WSU Data Analytics major, offered jointly by the Department of Mathematics and Statisticsin the College of Arts and Sciences and the School of Electrical Engineering and Computer Science in the Voiland College of Engineering and Architecture, is now available at WSU in Everett.
Students can transfer into the Data Analytics program from a variety of academic backgrounds, though additional time to graduation may be required if core coursework is lacking. The more core certification courses that are completed prior to transferring, the sooner you can certify in the program. Please talk to an adviser for detailed information on transfer credits and your estimated graduation date.
Core Certification Courses**
- CPTS/STAT 115 Introduction to Data Analytics
- CPTS/STAT 215 Data Analytics Systems & Algorithms
- MATH 171 Calculus I
- MATH 172 Calculus II
- MATH 220 Introductory Linear Algebra
- Choose one of the following:
- CPTS 131 Program Design & Development-Java
- CPTS 121 Program Design & Development-C/++
- Choose one of the following:
- CPTS 132 Data Structures-Java
- CPTS 122 Data Structures-C/++
**Equivalent course numbers will differ based on community college.
The WSU data analytics core curriculum and specialization tracks develop strong technical skills and working knowledge of an application area, combined with strong communication skills and the ability to work in teams.
The bachelor of science in data analytics requires:
- Core courses in mathematics, statistics, computer science, and philosophy
- Completion of a specialization track
- Satisfaction of WSU UCORE general education requirements
- Electives sufficient to complete a minimum of 120 credits overall
How to apply
1. Transcripts showing coursework to-date are required before your initial application can be evaluated. Prospective students should first meet with the WSU Everett data analytics program adviser to review your transfer credits.
2. APPLY using the Transfer Student Application.
– Select “WSU Everett” as your campus and “Data Analytics” as your academic interest.
3. Updated official transcripts will be required once grades are posted for spring and summer (if you enroll in courses). Contact all previous colleges and have them send official transcripts to:
Washington State University Everett
915 N. Broadway
Everett, WA 98201
4. The academic adviser will contact you and help you apply for certification into the Data Analytics program.
5. Pay the WSU tuition deposit, which confirms acceptance of your admission offer.
* NOTE: This deposit is nonrefundable; pay the deposit only after you are certified into the data analytics program.
WSU graduates will be trained in advanced statistical, data and computer science skills as well as concentrated domain knowledge, the ability to work in teams, and communicate effectively with colleagues and managers. Businesses across the Pacific Northwest and beyond need skilled professionals who can apply sophisticated data science techniques to meet industry needs. The potential career fields and industries listed below are meant to highlight possibilities, but this is by no means exhaustive. There are few fields or industries not impacted by big data.