Graduate Admissions

Earn an Advanced Degree

Graduate programs in the School of Computer and Data Sciences prepare students for a dynamic range of career opportunities. Possibilities span fields such as developing time-critical software for aerospace systems, synthesizing data streams to inform strategy or policy, designing graphics and animation software, securing networks and information systems, and building data-driven solutions using advanced analytics and machine learning.

Ready to apply? Start your application on Slate, the centralized application portal for graduate admissions at the University of Oregon.

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Application Deadlines

Unless otherwise noted, applications are only accepted for fall admission.

How to Apply

Fill out the Graduate Admission Application online. For more instructions, visit the University of Oregon Division of Graduate Studies website. The form may be left unfinished until the deadline. Applicants pay the application fee ($90 for international students, $70 for domestic students) upon completion of the online form. Note: Applications sent via mail but not submitted via Slate (online application) will NOT be considered.

See degree-specific requirements below for more detail.

Graduate Application Requirements: Computer Science and Cybersecurity

Applicants should submit the following materials with their applications for the computer science master of science (MS), computer science doctorate degree, and the cybersecurity MS:

• Personal statement
• Unofficial transcripts from all colleges or universities previously attended, including UO
• Contact information for recommendations
• Writing sample (optional)
• Resume or CV (optional)

Graduate Prerequisites: Computer Science and Cybersecurity

Applicants from a range of academic backgrounds should show preparation for graduate study and undergraduate-level expertise in the following:

• Principles of computer organization and operating systems
• Programming languages
• Program development and analysis
• Data structures and algorithm analysis

Students who have this expertise (and can document it via coursework or some other method) will be treated as if they have a computer science degree already. Students who do not have this expertise will still be considered, but, if accepted, they will need to take some undergraduate courses to attain the expect level of expertise.

The minimum required GPA for MS applicants is 3.0, and 3.5 or higher is preferred for doctorate applicants.

Graduate Test Scores: Computer Science and Cybersecurity

Note that TOEFL/IELTS/DET demonstrate proficiency in speaking English. Any person holding a degree from an English-speaking institution does not need to take these tests. Please see English Language Proficiency Requirement for International Applicants for additional information. 

Graduate Application Requirements: Data Science

Applicants submit the following materials with their applications for the Data Science MS

• Personal statement
• Unofficial transcripts from all colleges or universities previously attended, including UO
• Contact information for recommendations
• Resume or CV
• Statement of academic preparation

Graduate Prerequisites: Data Science

Incoming data science graduate students must have experience in at least one of the areas listed below (math, statistics, and programming) and be prepared to take courses in any remaining areas. Applicants will need to document this experience in the application process through a Statement of Academic Preparation. Students aiming to finish in one year must have sufficient experience in all three areas by the time they start the program.Incoming students aiming to finish in 1.5 or two years can take foundational courses to provide necessary background in math, stats, or programming during their first two terms of the program. Students should already have experience equivalent to at least one of the following classes, and evidence that they are ready for the other two.

1. Foundational Mathematics for Data Science (DSCI 625): Linear algebra, calculus, and introductory discrete math; specifically: vectors and matrix operations; linear transformations; eigenvalues/eigenvectors; continuous functions and limits; partial derivatives and Jacobians
2. Foundational Statistics for Data Science (DSCI 626): Reading and plotting data; p-values; type I/II error and power analysis; univariate linear models; bootstrapping; permutation testing; chi-squared for contingency tables; application of simple machine learning methods for prediction or classification
3. Foundational Programming for Data Science (DSCI 627): Introduction to data structures; algorithm analysis; version control; managing and sharing large datasets; python and jupyter notebooks for data wrangling

Statement of Academic Preparation: When you apply, you will let us know in your statement of academic preparation whether you have experience that covers the above areas: either a list of courses that covers a majority of the topics (with a course syllabus if possible), or a short narrative describing your equivalent experience. For instance, if you have not taken courses but have worked extensively with python on the job, then let us know the years of experience and types of tasks done using python. You and your graduate advisor will then determine whether it is necessary to enroll in any foundational courses.

Data Science MS Test Scores

Graduate Admissions FAQ

Below are a few frequently asked questions from potential SCDS graduate students.

What is the status of my application?

Your application goes through many checks, including a thorough review by multiple faculty members. This process takes time (applications may show as pending for some time), and little feedback is given. That said, if there is a problem with your application, you will be contacted by graduate admissions.

My undergraduate degree is not in data science or computer science. Is this OK?

We encourage applicants from a broad range of backgrounds who are strongly motivated to learn more. This might mean an undergraduate degree in data science, computer science, statistics, or mathematics. Or, it might mean that you've worked with the topic area in some other area and feel ready to dive deeper. The amount of preparation you need to be successful in the program is described above.

Where do I learn more about tuition and fees?

We recommend you look at the Office of the Registrar's tuition and fees information.

Where can I learn about graduate studies in general at University of Oregon?

We recommend you look at the Division of Graduate Studies website.

I am an international applicant. Where can I find more information?

We recommend you look at the International Student and Scholar Services website.