The advanced data science option targets students who seek to develop new data science methods and build new data science tools. It focuses on creating an inter-disciplinary cohort of data science students taking the same set of advanced data science courses. Click on the tabs below to find out more about the core curriculum, participating departments, and leadership structure.



Core Curriculum

Big Data is an evolving field, whose definition is fluid, and will continue to evolve over the years. Thus, the core of our educational approach is a comprehensive interdisciplinary, multifaceted practical training program.

  • Core Curriculum: An integrated, multidisciplinary set of courses that prepare the students in the algorithmic, statistical, systems, and scientific aspects of Big Data. This curriculum is an overlay on top of the requirements of the participating departments in a manner that is specific to each department. Please contact the faculty liaisons for detailed information.

Three out of four of the following core courses:

Data Management: CSE 544.
Machine Learning, CSE 546 or STAT 535.
Data Visualization: CSE 512.
Statistics: STAT 509 or STAT 512-513.

Course descriptions and pre-requisites are listed here.

Additionally, to further expand students’ education and create a campus-wide community, students register for at least 4 quarters in the weekly Big Data Seminar Course, CHEM E 599F.

An Advanced Data Science course can be replaced by an equivalent or more advanced course in the same area UPON APPROVAL. A student must submit an email petition to the Steering Committee (bigdata-igert-steering (at) cs (dot) washington (dot) edu) to perform such a substitution. The Steering Committee may request input from the student’s Faculty Advisor and the primary department’s Graduate Program Advisor before making a decision.


Departmental Requirements

Details for each department’s official Advanced Data Science Option can be found on their web pages:

Participating departments:

Applied Math: Contact people Lauren Lederer and Hong Qian. Details on the Advanced Data Science Option in Applied Math.

Astronomy: Contact person Andrew Connolly. Details on the Advanced Data Science Option in Astronomy.

Biology: Contact people Marissa Heringer and Tom Daniel. Details on the Advanced Data Science Option in Biology coming soon.

Chemical Engineering: Contact people Allison Sherrill and David Beck. Details on the Advanced Data Science Option in Chemical Engineering.

Computer Science & Engineering: Contact people Elsa Binag and Magda Balazinska. Details on the Advanced Data Science Option in CSE.

Genome Sciences: Contact people Brian Giebel and William NobleDetails on the Advanced Data Science Option in Genome Sciences.

Math: Contact person John Palmieri. Details on the Advanced Data Science Option in Math.

Oceanography: Contact people Michelle Townsend and Mark Warner. Details on the Advanced Data Science Option in Oceanography.

Psychology: Contact person Kristina Olson. Option has been approved, details should be available soon on Psychology department website.

Statistics: Contact person Ellen Reynolds. Details on the Advanced Data Science Option in Statistics.



Steering Committee:

Ginger Armbrust, Oceanography

Magdalena Balazinska, Computer Science & Engineering

David Beck, Chemical Engineering

Andrew Connolly, Astronomy

Tom Daniel, Biology

Emily Fox, Statistics

Carlos Guestrin, Computer Science & Engineering

William Noble, Genome Sciences

Hong Qian, Applied Math

Mailing List

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Development of the Advanced Data Science Option was partially supported by the following: