Summer Capstone Project

Get 1:1 mentorship on your Data Science project this summer!

We are launching a new data science mentorship program this summer! The Data Science Training Capstone program gives you an opportunity to work with DaSL instructors Chris Lo or Ted Laderas in a 1:1 mentorship to bring what you learned in our data science classes to a data science project in your professional work!

Over 6 weeks, you will receive individualized guidance to tackle a data science problem in your professional work that relates to your data science classroom experience with us. We will help you formulate a data science plan in your project, provide starter code, help you troubleshoot, and ultimately you will in charge of writing your own code and interpreting the results.

Deadline for submissions: May 1.

Eligibility

To participate in this program, you must:

  • Have taken at least two classes with us by the end of the 2026 Spring Quarter (such as Intro to R/Python/SQL, Intermediate R/Python, Bash for Bioinformatics, Bioconductor for Genomics, Machine Learning for Python)
  • Be available between June 15 and July 24
  • Have a project with a dataset in mind

If this is you, please fill out this intake form by May 1.

Due to the pilot nature of this capstone project, we can only accept a small cohort of students this summer, so we may need to prioritize projects in the application process.

What kinds of capstone projects are we looking for?

CriteriaGood FitPoor Fit
Connection to DaSL TrainingThe project connects directly to what the participant learned in the classroom and expands upon it, such as using functions and iteration in R on a large dataset.The goal of the project is unrelated to what the student learned in the classroom, such as comparing statistical models in R.
Feasibility of projectThe project has specific scientific goals and/or educational goals that is feasible within a 6-week timeframe. The project leverages the expertise of the participant’s and mentor’s backgrounds.The project has vague scientific or educational goals outside the scope of a 6-week timeframe. The project involves expertise outside of the participant’s and mentor’s backgrounds.
Relevance of datasetThe participant has reasons that the dataset can help achieve the goals of the project.The participant is unsure the dataset can help achieve the goals of the project, or the data is not available for use.

Application process

What to expect in this application process:

  1. Fill out the intake form by May 1.
  2. If a good fit, we will meet up to brainstorm how the project can be feasible in a 6 week period, and plan out a more formal proposal together.
  3. We will ask you to fill out a capstone project proposal form.
  4. If accepted, we will edit and finalize the scope of the project for approval.