Course substitutions are allowed, but must be approved by the faculty curriculum committee. The curriculum committee meets once a quarter to review petitions.
You will need to state which minor requirement you believe the course fulfills and write a statement explaining why you believe this course is an appropriate substitution.
Data Studies courses must cover content regarding the conceptual and theoretical foundations for understanding the role of data in knowledge production (either within specific domains or more generally) and promote critical reflection on the ethical, social, cultural, and political dimensions of data.
Data Skills courses must cover content such as programming, data acquisition, and management practices, software tools common to data science, statistics, machine learning, data visualization, and qualitative analysis.
Cross-cutting courses use theories, questions, and data that are relevant to the domain alongside data science knowledge and skills.
The capstone is a required course for all students to complete the minor. This course is only offered in Spring quarter once per year. The exact day and time of this course is announced in Winter quarter. If you are unable to take the capstone course, you can submit a petitions for an alternative capstone experience for the following reasons:
Your petition must include a letter (can be an email) from your major adviser supporting your reason for needing the alternative capstone experience. We recommend you submit the petition at least one quarter prior to your graduating quarter. The alternative experience is online and asynchronous and will be due by week 3 of the quarter in which you are graduating.
Fill out the petition form here. In the form, you will be asked to explain your reason and upload the letter from your major adviser.
A data science minor adviser will then send you the alternative capstone instructions.
Faculty are welcome to submit a course to be added to the Data Science curriculum list. Please email dataminor@uw.edu for more information.
Leverage familiarity with data science in fields outside of data science, and gain skills and fluency to work with data in your major domain of study.
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