At the University of Washington, we think students from all domains will benefit from acquiring skills in Data Science. To address this need, the eScience Education Working group has brought departments together from around campus to create a template for scalable, university-wide program. The key idea behind undergraduate education at UW is the following:

  • Interested departments extend their core major program with a data science specialization in the form of a “Data Science Option”. The option, or specialization, appears on the student’s transcript.
  • Each data science specialization covers the same set of core data science topics, detailed below.
  • Each department, however, chooses how best to cover the below topics in a way that makes most sense for their students. Departments also have additional, domain-specific requirements.

At the undergraduate level, a student who will earn a data science specialization must complete courses in the following areas:

Required areas with recommended courses:

  • Programming: e.g. CSE163 or CSE143
  • Machine learning: e.g. CSE416/STAT416, STAT435, INFO 371
  • Societal implications of data science: e.g. SOC 201: Special Topics (Topic: Data and Society)

Required to cover at least two areas:

  • Data management: e.g. CSE414 or INFO 445
  • Data visualization and communication: e.g. CSE412, INFO474, or HCDE411
  • Advanced statistics and probability: Department-specific course choices

Optional:

  • Introduction to data science: e.g. STAT180/CSE180/INFO180
  • Other department specific requirements

For questions about the program, please contact Magdalena Balazinska or David Beck.

Participating departments and their undergraduate data science options are as follows (alphabetical order):

Students interested in learning data science methods and tools who are in a department or school that currently does not offer a data science specialization are encouraged to take the above courses as electives in their existing majors.