Students can complete the ELC requirement in a variety of ways:

1. Participate in a Brown University credit experience (i.e. independent study):
   1. Complete a one-semester independent study for credit that focuses on research in data science or applies data-science techniques to a problem in the student’s concentration (e.g. as part of the student’s honors thesis, though this is not required).​
   2. Be a Data Science Fellow. Students may complete DATA 1150 and the concurrent Data Science Fellows project to fulfill both the elective and experiential components of the certificate.
2. Participate in a non-credit experience such as:
   1. Completing a data-related summer internship
   2. TA-ing for a data-related course (TA'ing for any of the DATA courses or courses on the certificate's elective list fulfills this requirement)
   3. Working with a local organization on a data-related project. 

Students who choose a non-credit option will be required to complete a reflective essay on their experience. This essay is due in your last semester (last day of November for December graudates and last day of April for May graduates). Read more about the requirements for this reflective essay below. 

• Students are responsible for identifying an appropriate experiential learning  component.
• Students must submit their proposal for their experiential component by the end of their sixth semester.
• Students should normally complete the experiential learning component during the summer following their junior year or during their senior year. The experiential learning component must be approved in advance by the student’s certificate advisor. Students will be asked to prepare a detailed proposal that explains how the experiential component draws on data science and how it relates to their concentration.

Reflective Essay Requirements

• Students who choose to pursue a no-credit option for the experiential learning component requirement must write and submit a 10-12 page paper by the end of their last semester (by November 30 for Fall graduates and by April 30 for Spring graduates).
• The essay should:
  • Describe your internship or project. Explain the nature of the work you completed and the project's primary objectives - did some of these objective compete with each other and if so, how? Be sure to highlight the specific data science or data-driven components of the work.
  • Reflect on the broader significance. Discuss the larger implications of the project and its potential impact on individuals, communities, or society at large. Consider how your project fits into the wider process of generating, analyzing, or disseminating  knowledge.
  • Draw connections. Explore how the project relates to the Data Fluency Certificate Learning Goals, the certificate coursework, your concentration, and your future academic or professional goals and plans.
• The report should be submitted online as an uploaded file under the heading "Non-credit Capstone Option" in the Data Fluency Certificate declaration on ASK. Here is a guide on how to upload the paper in ASK: https://ithelp.brown.edu/kb/articles/students-update-your-course-plan-in-ask. Please contact us at dsi-ug-certificate@brown.edu if you have any trouble. 

Coming soon! 

Have a question about the Experiential Learning Component that wasn't addressed above? Please review our Certificate FAQ page and reach out to dsi-ug-certificate@brown.edu if you still have questions!