11-632: Data Science Capstone - Syllabus
Time & Location
Section A: M/W 10:10 am – 11:30 am, TEP 1403
Contents and Schedule
Student teams will work on their assigned Capstone projects under the supervision of the project advisor and, where applicable, in collaboration with other students/faculty.
Class sessions are noted on the scheduled dates below. Professor Nyberg is available for office hours during class meeting time in the assigned classroom (TEP 1403). Teams are encouraged to come to class to work on their projects and/or ask questions.
All deliverables are bolded. Students are expected to meet as project teams at least once a week, record, and submit a 5 to 10-minute weekly standup. There are three evaluation milestones, a draft, and final report, and a final presentation.
All italicized text is for your notice.
| Date | Activity | Deliverable Due |
|---|---|---|
| Aug 29 | Introduction/Overview | |
| Aug 31 |
Tutorials:
|
Fall Plan Due Sep 4 |
| Sep 5 | Labor Day (No Class) | |
| Sep 7 | Fall Plan Feedback | |
| Sep 12 | Work with Team and Mentor; Prof. Nyberg Office Hours (in-person, in the classroom during class time) | |
| Sep 14 | Work with Team and Mentor; Prof. Nyberg Office Hours (in-person, in the classroom during class time) | Weekly Standup Due Sep 15 |
| Sep 19 | Work with Team and Mentor; Prof. Nyberg Office Hours (in-person, in the classroom during class time) | |
| Sep 21 | Work with Team and Mentor; Prof. Nyberg Office Hours (in-person, in the classroom during class time) | Weekly Standup Due Sep 22 |
| Sep 26 | Work with Team and Mentor; Prof. Nyberg Office Hours (in-person, in the classroom during class time) | |
| Sep 28 | Work with Team and Mentor; Prof. Nyberg Office Hours (in-person, in the classroom during class time) | Weekly Standup Due Sep 29 |
| Oct 3 | Work with Team and Mentor; Prof. Nyberg Office Hours (in-person, in the classroom during class time) | |
| Oct 5 | Work with Team and Mentor; Prof. Nyberg Office Hours (in-person, in the classroom during class time) | Weekly Standup Due Oct 6 |
| Oct 10 | Work with Team and Mentor; Prof. Nyberg Office Hours (in-person, in the classroom during class time) | |
| Oct 12 | Work with Team and Mentor; Prof. Nyberg Office Hours (in-person, in the classroom during class time) | Weekly Standup Due Oct 13 |
| Oct 17 | Fall Break (No Class) | |
| Oct 19 | ||
| Oct 24 | Midterm Check-in with Prof. Nyberg (in-person and Zoom) Schedule TBD |
Midterm Grades due to University Oct 24 |
| Oct 26 | Midterm Inner-team Peer Review due Oct 27 | |
| Oct 31 | Work with Team and Mentor; Prof. Nyberg Office Hours (in-person, in the classroom during class time) | |
| Nov 2 | Work with Team and Mentor; Prof. Nyberg Office Hours (in-person, in the classroom during class time) | Weekly Standup Due Nov 3 |
| Nov 7 | Work with Team and Mentor; Prof. Nyberg Office Hours (in-person, in the classroom during class time) | |
| Nov 9 | Work with Team and Mentor; Prof. Nyberg Office Hours (in-person, in the classroom during class time) | Weekly Standup Due Nov 10 |
| Nov 14 | Work with Team and Mentor; Prof. Nyberg Office Hours (in-person, in the classroom during class time) | |
| Nov 16 | Work with Team and Mentor; Prof. Nyberg Office Hours (in-person, in the classroom during class time) | Weekly Standup Due Nov 17 Draft Report Due Nov 20 |
| Nov 21 | Thanksgiving Break (No Class) | |
| Nov 23 | ||
| Nov 28 | Work with Team and Mentor; Prof. Nyberg Office Hours (in-person, in the classroom during class time) | Draft Report Feedback will be returned by Nov 28 |
| Nov 30 | Work with Team and Mentor; Prof. Nyberg Office Hours (in-person, in the classroom during class time) | Weekly Standup Due Dec 1 |
| Dec 5 | Work with Team and Mentor; Prof. Nyberg Office Hours (in-person, in the classroom during class time) | |
| Dec 7 - Dec 14 | MCDS Capstone Final Presentation | |
| Dec 15 | Team Peer Review Due Final Report Due Final Inner-team Peer Review Due |
|
| Dec 21 | Final Grades due to University | |
Assessment
The grade will consist of an assessment of both the quality of the data science experiment, its results, the technical process over the course of the semester as well as your evaluation by your peers.
The course grade will be based on the following:
- Fall Plan (required, feedback provided): 0%
- Weekly standups (start September 15): 10%
- Midterm check-in: 10%
- The draft report is expected to be content-complete, i.e., no missing results, no missing sections, no text with grammatical issues as well as understandable diagrams and proper treatment of related work: 10%
- Final report is where you work out issues that arise during your final presentation, which will be graded as if it were submitted to a peer-reviewed workshop. You will also receive reviews from 11-631 students: 30%
- Final presentation: 30%
- Team Peer Review: 5%
- Midterm Inner-team Peer Review: 2.5%
- Final Inner-team Peer Review: 2.5%
Students are expected to take ownership of the project, take the initiative in driving the development forward and autonomously seek help when getting stuck. If requirements are unclear at any point, please talk to your project mentor or the instructors. For a detailed rubric of how the system, experiment, and results are assessed, you will be directed to the grading criteria document as posted on Canvas during the semester.
Technical Process Criteria
The Capstone project is also an exercise in proper software engineering. Your technical process evaluation will consider the following factors:
- Every project is required to use a GitHub or bitbucket repository.
- Every team member is expected to produce regular and sensible commits.
- To do items and nontrivial ongoing tasks are to be organized and documented in the GitHub issue system. This documentation is particularly important for planning milestones and action items produced during weekly meetings.
- Documentation must include a plan with timelines and milestones. Time and labor estimates for tasks are also a critical part of a project plan.
- Any documentation that will be needed on an ongoing basis (e.g., APIs, file formats, etc.) is to be kept in the GitHub repository readme and/or wiki pages.
- Code quality will be accounted for by the mentor and/or peer review.
Weekly Standups
A standup is a casual check-in to share your team’s progress update. It is not supposed to be a polished presentation. Simply share your screen and brief us on what has been happening. Be authentic with what your team’s current progress is and what your team is dealing with. Doing so allows us to provide you with timely support if needed.
Each team is required to submit a standup on a weekly basis according to the course schedule. Students submit standups by recording a 5 to 10-minute video.
Midterm Check-in
Midterm check-in is a standup-style, in-person (or synchronous via Zoom) meeting with professor Nyberg. The schedule for these meetings will be posted on Piazza.
Inner-team Peer Review Assessment
To facilitate a fair distribution of work among team members, each midterm and final assessment includes a peer review. It includes
- Evaluation of one’s own and other’s contributions to the project.
- Comments about my own contribution to peers.
- Comments to peers about peer contribution.
- Comments to instructors about their own and others’ contributions.
Team Peer Review
Each student is required to attend at least one final presentation of another team and submit a brief review of this team’s presentation. Students will have the chance to submit their preference for the team to review according to their schedule suitability.
Academic Integrity
For all presentations and the final report, students share work with their teammates. Both presentations and reports need to make clear at all times the students’ contributions and those parts that have been influenced, taken, adapted, or otherwise derived from prior work. Any such additional material must be properly cited in the report and on the presentation slides. This citation material includes related academic writing (even if published by a collaborator of the project), diagrams, datasets, prior Capstone project reports, video tutorials, scientific blog posts, and technical components such as algorithms, libraries, and the like. When a source’s text is paraphrased, it needs to be referenced. If it is reused verbatim, it must be quoted.