B.S. Honors Program

The Data Science B.S. with Honors provides students with an opportunity to deepen their knowledge of data science and its applications, engaging in advanced learning, independent studies, and research.

Requirements

In addition to meeting all requirements for the BS in Data Science, the student must:

1. Maintain a GPA of at least 3.5 in coursework in the major.
2. Choose a concentration, describe it in the honors proposal, and have it approved by their faculty advisor. Submit the honors proposal by the final study list deadline at least two quarters before they intend to graduate (typically autumn quarter during the senior year). 
3. Complete 15 units of relevant upper-level coursework, as outlined in the honors proposal, including  6 units of independent work. 
   
   Here are some guidelines on concentration, class choices, and the honors proposal.
   1. Given the interdisciplinary nature of Data Science and of the major, achieving greater depth and understanding in one area of data science will typically require taking additional courses. These upper level classes will be chosen in collaboration with the major advisor and will constitute a coherent concentration in an area of interest. Note that the chosen area can be in the foundational disciplines of data science (allowing students to engage more closely in the development of new methods) or in applications (giving students the opportunity to become intimately familiar with a class of the scientific/operational challenges that might be addressed with data science).
   2. At least 6 of the 15 units need to be obtained with an educational experience that requires substantial independent work: a small group seminar (e.g. BIODS 290 or Stats 319), a research-based course, an independent reading/research course (e.g. DATASCI 199)
      1. The faculty supervising the student in this independent effort will be the “research advisor” for the student and will need to be identified in the  honors plan. 
      2. While not required to, students can elect to write a thesis, under the supervision of their research advisor, after obtaining the program approval. 
         1. If a student is doing a thesis, they can take DATASCI 120 (Data Narratives) while they write their thesis. This course can count toward the 15 honors units and double-count as the WIM. This is the only instance in which a course can double count between a regular major requirement and honors requirements. 
         2. If doing a thesis, and with the major advisor’s approval, up to 15 research units can be used to complete the upper level course requirement. If not doing a thesis, students who are interested in completing more than 6 units of independent work need to obtain permission from the major advisor.
4. Assemble a final portfolio which showcases the student’s achieved ability to think independently and creatively using the tools of data science. Specific instructions for the portfolio will be provided to students (including timeline for submission and guidelines). The portfolio will have two components:
   1. Documentation of the independent work experience (poster,  video of oral presentation, paper or honors thesis, etc.).  Note that support for thesis writing (if this option is selected) will be provided in the class DATASCI 120 (Data Narratives). 
   2. A self-reflection essay, in which students must do the following:
      1. Explain their choice for honors concentration topic, how it relates to their interests, and how it fits into Data Science.
      2. Describe how each course selected added to the student’s knowledge and understanding in the area chosen for honors concentration. How did the skill and knowledge acquired via the honors curriculum contribute to the student’s understanding of data science and their self-positioning in this field? 
5. Participate in the annual Data Science Capstone Showcase in May or June, where all students who have completed a capstone experience will share their learnings with posters, oral presentations, or other media.

Honors Concentration Examples