Tuesday, April 23 -- Thursday, June 27, 2019
A mentored group project based on real data and questions from a partner within or outside the university. Students will formulate questions and design and execute a suitable analysis plan. The group will work collaboratively to produce a final product(s) to deliver to the capstone partner.
By the end of the course, students are expected to be able to:
- Identify an interesting data science question for which data are available or obtainable.
- Define the scope of a possible solution, identify units of work (deliverables), and estimate the effort required.
- Design and implement a solution to a problem in data science that can be completed within 6 weeks.
- Function effectively in teams: communicate productively between team members, identify sub-problems that could be worked on individually by team members, and integrate contributions of team members into a final product.
- Document and present (using written, oral, and visual means) the process and results from a solution to a data science problem.
- Evaluate or assess a solution to a data science problem, and compare it with alternative approaches.
The general steps involved in this capstone course are:
- After the Capstone fair, you will rate/rank the project proposals. You will then be assigned to a project/team. These assignments will be based mainly on the ratings but the instructors may influence the assignments in order to create teams that we think will work together effectively.
- Meet with your MDS mentor and the Capstone partner (before the course start date). Establish regular meetings.
- Propose the data product and approach. (~2 weeks)
- Work with your team, colleagues, and mentors to develop an approach in a 2-day hackathon.
- Orally present the proposal at UBC, to solicit ideas and feedback.
- Write the proposal. This will be passed to the capstone partner to check that your approach and (mostly) your proposed product is indeed in line with the capstone partner's needs.
- Develop the data product (~6 weeks). This involves:
- Regular meetings with the mentor.
- Regular meetings with the mentor and capstone partner.
- Polish the data product for delivery to your capstone partner (~2 weeks).
- Present your final data product and approach to the class.
- Deliver the data product after incorporating feedback from mentors and colleagues, along with a final report.
- Briefly present your product(s) in an end-of-program celebration (not graded).
- Reflect on the project in a short individual report.
The deliverables are listed below:
| Topic | Submission | Due date | Weight |
|---|---|---|---|
| Proposal presentation | Group | Friday April 26, 2019 2-4pm | 5% |
| Proposal report | Group | Tuesday April 30, 2019 12:00 -- to mentor Friday May 3, 2019 12:00 -- To partner |
5% |
| Final presentation | Group | Monday and Tuesday (June 17-18, 2019) | 20% |
| Final report | Group | Friday June 21, 2019 18:00 -- To mentor Wednesday June 26, 2019 18:00 -- To partner |
20% |
| Data product | Group | Wednesday June 26, 2019 18:00 -- To mentor Wednesday June 26, 2019 18:00 -- To partner |
30% |
| Teamwork | Individual | Thursday June 27, 2019 12:00 noon | 20% |
| End-of-year presentation | Your choice | Thursday June 27, 2019 at the end-of-program celebration | N/A |
For more information on each deliverable, see the descriptions in the deliverables directory.
| Date | Event | Location |
|---|---|---|
| Tuesday-Wednesday April 23-24, 2019 | Hackathon | ORCH 3018 and ORCH 3074 |
| Friday April 26, 2019 from 2-4 pm | Proposal Presentations | ORCH 4018 and 3074 |
| Fridays from 2-4 pm | Capstone Seminar Series | DMP 301 |
| Monday-Tuesday June 17-18, 2019 from 9am - 3pm | Final Presentations | DMP 301 (Monday) and ORCH 4074 (Tuesday) |
| Thursday June 27, 2019, 5:30pm - 7:30pm | End-of-program celebration and mini-presentations | ESB atrium |
The regular policies hold during the capstone course. Especially pertinent is the expectation that you work on the capstone project full time.