Partnership policy

Working together

Agree on the work split, check-in times, and where you will keep the notebook. Review each other’s work before submitting.

If a partnership problem persists, contact the course staff promptly through a private Ed post. A CA can help you work through it or discuss continuing solo.

Science: You may extend your Project 1, choose either partner’s Project 1, or start fresh. Your dataset must meet the Project 1 requirements for table count and data size.

Submitting as a team

1. Put both partners’ names at the top of the notebook.
2. One partner uploads the .ipynb to Gradescope.
3. Add the other partner as a group member and check that both names appear on the submission.

Late days

Each student has 2 project late days for the quarter, shared across Project 1 and the Project 2 final. PSET late days cannot be used for projects.

Proposal: No late days.

Final: Submit once per team. Each late day uses one day from both partners, so your team can use only as many days as the partner with fewer remaining.

For example, if you have two days left and your partner has one, your team can use one late day without penalty. Both partners spend one day. Solo students use their own remaining balance.

After your team’s late days run out:

• Within the next 24 hours: receive 80% of your earned final-submission score.
• After that: receive no credit for the final submission.

Proposal points are unaffected. Each late day adds 24 hours to the posted 11:59 pm Pacific deadline, including weekends and holidays.

For extenuating circumstances, only the head CA can grant additional extensions. Contact them through a private Ed post before the deadline, or as soon as you can if circumstances prevent that.

Sharing notebooks and data

Both tracks: Share the Colab notebook with your partner and coordinate edits and runs. You can also use local Jupyter and Git; submit one executed notebook with the required outputs saved.

Science: Sharing a notebook does not grant BigQuery access. For an existing shared output dataset, give your partner BigQuery Job User on the project and BigQuery Data Editor on that dataset. They also need read access to any private source tables. See BigQuery access roles.

Systems: Run locally or in Colab. Follow your tier’s dataset and memory requirements.