Capstone Project Proposals for Spring 2025 are now open.

The soft deadline for UBC Capstone proposals is Nov 1st. And the hard deadline is Nov 29th. Proposals sent in by Nov 1st will receive feedback (that will hopefully increase their chances of being selected).

Partners may choose to submit a capstone project(s) to the MDS Computational Linguistics program (language-related data science) and/or the MDS Okanagan/ MDS Vancouver programs (general data science).

Proposal forms can be found here:

You can view an example proposal here.

Should I submit my proposal to MDS Okanagan, MDS Vancouver or MDS Computational Linguistics?

The MDS Computational Linguistics (MDS-CL) program specializes in topics focusing on analyzing language/text/speech-related data and building models that can extract insights from this data. Our students take general data science courses in the first half of the program and then specialize in linguistic analysis in the second half of the year. Particular areas of expertise include deep learning, sentiment analysis, and multi-lingual methods such as machine translation. You can read more about the program here and can see the MDS-CL capstone page to learn more about the type of projects MDS-CL addresses in capstone.

The MDS Vancouver (MDS-V) and MDS Okanagan programs covers a general overview of data science, including topics of data wrangling, visualization, dashboards, statistics and machine learning, amongst others. You can read more about the programs and can see their capstone information on their respective websites to learn more about the type of projects MDS-V and MDS-O addresses in capstone.

Instructions for filling out the capstone proposal form

Detailed instructions for filling out the capstone proposal form can be found below.

About your organization

Briefly introduce your organization.

Brief description of the problem/question

Include a brief description of the problem. If you’d like, you can suggest approaches that the students can take to address the problem, but this is not necessary.

Available data

Describe the data that you will make available to the students:

  • How much data is there?
  • Do you have an existing data dictionary/data schema?
  • What type of features are available?
  • How clean is the data?
  • In what form will the data be available to the students?
  • Does your organization provide any computational resources (e.g., cloud computing, virtual machines) to handle large scale data analysis?

Expected Project Deliverables

What product(s) would you like to receive from our students, and what (in general) should it communicate or have the ability to do? Examples:

  • A dashboard, such as a Shiny or Dash app, to explore an aspect of your data.
  • An R or Python package with documentation to simplify an analysis.
  • A data pipeline that includes some data science model
  • A report outlining student findings

Be as precise as possible; data expectations can differ from field-to-field. If you have 150 documents/sentences/paragraphs, etc., state that. The types of methods that can be applied differ widely, dependent on the amount of annotated data.

If your project requires confidentiality and IP assignment, please read our legal page on how we handle these before submitting your capstone proposal. During the proposal submission, we will ask you which types of agreements are necessary for working on the project. For non-UBC Capstone partners whose projects require confidentiality and IP assignment, we strongly recommend that partners show the UBC template documents to their legal counsel and get their agreement to use these documents before submitting the capstone proposal. If you wish to use your own NDA/IP agreement, this must be included in your application. Only legal documentation attached as part of the proposal will be considered for use.

We understand that you may require some restrictions to be put in place, but we also would like for our students to have some freedom to talk about the work they’ve done when applying for jobs. We want our students to know about these restrictions up-front so that they can make an informed decision about the project. In the proposal, please be as concrete as possible: do you anticipate students will be able to open-source the code they write? Publish a blog post about their work? Discuss it in a private job interview?

This section should also include any other requirements of students participating in the project, like background checks, etc.

Conflicts of interest

Declare any conflicts of interest. For example, if a current MDS student or family member is involved with your organization on a professional or personal level, this should be declared along with a short explanation. These situations are generally not problematic, but we prefer to disclose them to the students before they rank the projects.