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Ecampus Data Analytics M.S. or Certificate

Resources for prospective students

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A career-ready foundation in data analytics

The demand for professionals who can interpret large quantities of data has never been greater, and these skills are vital for scientific advances and business success worldwide. Whether you're an experienced analytics professional or looking to change careers and become one, you can chart your path forward by earning a Master of Science degree or a Graduate Certificate in Data Analytics online from Oregon State University's top-ranked Ecampus program.

The certificate program is an 18-credit online program that covers the basics of statistical analysis and computer programming. The M.S. in Data Analytics program is a 45-credit online graduate degree that includes the certificate content plus additional content on additional advanced and specialized statistical methods.

Preparing for data analytics admissions

The Data Analytics programs admit applicants for Fall term only. The current application period opens in mid-September for the program that starts the following September.

The deadline to apply is April 1st.

If you will not have completed the ST 351 prerequisite course before the application deadline, it would be advisable to apply much earlier (ideally by February 15) in case you are admitted with the provision that you take the course in spring or summer term before starting the program in fall term.

Learn about the admission process, onboarding, support and more!

The statistics department prepares guidebooks for our prospective and current students to help acquaint you with the organization, policies, and procedures of the Data Analytics program at Oregon State University.

Data analytics M.S. learning outcomes

  1. Gain a thorough understanding of applied principles of statistics.
  2. Demonstrate the ability to summarize a technical report and/or statistical analysis and interpret results; also, show the ability for broader implication of application in the statistical field.
  3. Communicate statistical concepts clearly and professionally in oral form.
  4. Demonstrate preparedness to provide guidance in statistical design and analysis.