Advanced Data Science Option


The Advanced Data Science option aims to educate the next generation of thought leaders who will both build and apply new methods for data science. This option will help to educate and recognize PhD students whose thesis work focuses specifically on building and using advanced data science tools. The goal of this option is not to educate all students in the foundations of data science but rather to provide advanced education to the students who will push the state-of-the-art in data science methods in their domain.

The Advanced Data Science option replaces the previous Big Data track introduced in 2014. This is an official UW degree option which will appear on your transcript.

Students enrolled in this option can expect to interact with students enrolled in similar Advanced Data Science PhD options in Computer Science, Statistics, Oceanography, Chemical Engineering and Astronomy.  Formally, the option is affiliated with an NSF IGERT training award in Big Data, and PhD students in the track are eligible for funding via that award. In addition, the track is designed to complement the activities of the eScience Institute and to leverage ongoing activities associated with the Moore/Sloan Foundation Data Driven Discovery Initiative, involving the University of Washington, New York University and the University of California, Berkeley.


Students with an interest in the Advanced Data Science option but only limited experience in this area should take preparatory coursework before attempting the ADS courses. Please contact Bill Noble for suggested courses.


Genome Sciences students who choose to enroll in the Advanced Data Science option must have approval of their thesis advisor and should then let Brian Giebel (bgiebel [ a t ] know they are planning to follow this option. There is no additional admission procedure.


Any Genome Sciences faculty member may serve as advisor to students enrolled in the Advanced Data Science option, although the student’s committee must include at least one of the following faculty members: Tony Blau, Jesse Bloom, Elhanan Borenstein, Joe Felsenstein, Phil Green, Gail Jarvik, Su-In Lee, Bill Noble, or Larry Ruzzo.

Training Grant:

For information about the new Big Data in Genomics and Neuroscience Training Grant, please see the BDGN website.

Course Sequence:

Students who choose to follow the Advanced Data Science option of the Genome Sciences Ph.D. program should follow the regular Genome Sciences course sequence but also include the following course requirements:

1. Instead of Genome 560: Statistics for Genome Sciences (typically offered Spring Quarter), students enrolled in the Advanced Data Science option should take Statistics 509: Introduction to Mathematical Statistics. Statistics 509 was most recently offered during Autumn Quarter, but you should check the Department of Statistics website or the UW Time Schedule to see when it will next be offered. Please note that this course requires significant use of calculus. If you have not taken calculus for some number of years, you might want to consider taking a refresher course beforehand.

Alternatively, for a more advanced approach, students may choose to take Statistics 512: Statistical Inference. In this case, students may wish to consider also taking Statistics 513, the second course in this sequence.

2. Genome 540: Computational Molecular Biology (typically offered Winter Quarter each year)

3. Electives:
Students must take 2 of the following three courses:

Data Management: CSE 544.
Machine Learning, CSE 546 or STAT 535
Data Visualization: CSE 512.

4. Additionally, to further expand students’ education and create a campus-wide community, students will register for at least 4 quarters in the weekly eScience Community Seminar.

Please check the UW Time Schedule or the Department of Statistics and Department of Computer Science & Engineering websites for information on when these electives are offered.

Frequently Asked Questions:

Do I need to complete this coursework during my first year?
No. You are welcome to enroll & complete the course sequence at any time during your graduate studies. A good time to enroll might be at the end of year one, once you have selected a thesis lab, although you may end up completing some of the required courses (for example, Genome 540), during your first year.

How do I apply?
Simply obtain your thesis advisor's permission and then contact Brian Giebel (bgiebel [ a t ] to let him know you are planning to follow this option.

I don't have an extensive background in Data Science but I am interested in learning more about this field. Is this the right option for me?
There will be a more general Data Science option introduced within the next year. This will likely be a better option for students with some interest in the field but without an especially strong background in this area.

Which courses should I take as prereqs in preparation for enrolling in this program?
Please contact Bill Noble for suggested courses.