Perform Large-Scale Data Analysis, Manipulation and Presentation
Next start date
September 28, 2017
The R programming language has become a vital tool for extracting useful information from large data sets across industry, academia and scientific research circles. R offers powerful statistical techniques, elegant data visualization capabilities, high extensibility and an active community that generates code packages for anyone to use.
In this three-course certificate program, we’ll cover how to perform sophisticated data analysis and modeling using statistical tools and R programming. You’ll gain advanced skills in data mining and big data management and discover how to produce insightful visual presentations. Develop the capabilities to solve complex problems using R.
A wide range of technically oriented professionals who want to analyze and derive meaning from large data sets.
Applicants must have a college degree and must have successfully completed, at a minimum, a college-level calculus class and a college-level statistics class. If your statistics coursework is five or more years in the past, we would encourage you to take another introductory statistics course prior to entering the program.
Applicants must also complete the math skills self-test.
Some experience with computer programming is strongly preferred, but not required.
If you're not a native English speaker, you’ll need to have at least basic English language skills to enroll. To learn more, see English Language Proficiency Requirements.
International students are welcome to apply to an online offering of this program, which doesn’t require a visa. To enroll in a classroom offering, you must have a visa that permits study in the United States. This program does not enable students to obtain or maintain F-1 visa status. For more information, see Admission Requirements for International Students.
Students must have access to a computer, an Internet connection, and a copy of open-source R for each course session.
You earn the certificate by successfully completing all required courses. For more information, see Completing Your Program.
Complete the courses listed below to earn the certificate. You may be able to take individual courses without enrolling in the certificate program; check the course pages for details.
Introduction to Statistical Analysis With R
Data Analysis & Modeling With R
Advanced R Programming & Graphics
Certificate in Statistical Analysis With R Programming
Approved by the UW Department of Statistics.
View this program's advisory board.
Each of our programs uses an advisory board to review content, guide design and recommend updates to ensure the program remains current as the field of study evolves. By tapping the minds of the top thinkers, doers and leaders in the field, we offer a transformational learning experience. The following individuals serve as the advisory board for this program.
Rovy Branon, Vice Provost, University of Washington Continuum College
Stan Humphries, Chief Economist, Zillow
Corinne Mar, Research Scientist, Center for Studies in Demography and Ecology
Tyler McCormick, Associate Professor, UW Department of Statistics
Vladimir Minin, Associate Professor, UW Departments of Statistics and Biology
Steven Murray, Global Head of Strategic Asset Allocation, Russell Investments
Thomas Richardson, Chair, UW Department of Statistics
Erin Shellman, Data Scientist, Zymergen
Ben Starsky, Professional Programs Manager, UW Professional & Continuing Education
Guy Yollin, Data Science Consultant, Milliman
Date: Thursday, June 29, 2017
Time: 12:00 p.m.–1:00 p.m. Pacific Time
Download the application form (PDF)
Apply online, or submit an application packet that includes:
We’re currently accepting applications and will be reviewing them in the order they’re received. We’ll accept applications until the program closes.
We’ll contact you within two weeks of receiving your application materials to let you know if you’ve been accepted to the program.
If you’re accepted, we’ll send you details about your first-term course, including information on paying your course fee. Your course fee is due four weeks before the first class.
With the exception of the one-time application fee, certificate program fees are charged on a quarterly basis. Payment is due when you register.
Course fees do not include any costs for class materials such as textbooks and software.
Drops, Withdrawals & Refunds
Attend class in person at one of our convenient locations. You’ll engage face to face with your classmates and instructors as part of a highly interactive curriculum. An online learning management system may be required to access some course materials and assignments.
Courses are offered 100 percent online. The flexible online format allows you to access course content wherever you are, on your own schedule. You simply need to complete assignments by their due dates. Video lectures, assignments and other course materials are delivered through a Web-based learning management system, such as Canvas or Moodle, which also serves as a hub for communicating with your instructors and classmates. You can stream video lectures as they are delivered live or view recordings at a later time.
Our special blended programs combine the convenience of online study with the vibrancy of in-person classes for a unique learning experience.
Not available for this program
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If you’re thinking about heading back to school, you’re probably also wondering how you’ll pay for it. To help you figure that out, we’ve put together a list of ways to help fund your education.
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