Running Data Science Teams
Class Coverage
- Lecture: How do we run a data science project? What skills are necessary on AI teams? How can/do data scientists work effectively with other roles?
- Goals: Initiate Q1 Project team groupings and discuss team roles.
Pre-Class Readings
Please read the following:
- Taxonomy of AI Risk (NIST)
- Improving Fairness in Machine Learning Systems: What Do Industry Practitioners Need? (Holstein et al.)
Participation Questions
- Review Replication Part 01 and complete “Section 1,” which contains discussion questions at the end.
- Submit Jupyter Notebook with discussion questions answered, to Gradescope by Thursday November 2nd, 2023 by 11:00am PT
This Week’s Slides
Assigned for Week 05
- Complete next week’s readings
- If you signed up to present on “Big Data’s Disparate Impact” (Barocas and Selbst) come prepared to present next week and submit your presentation on Gradescope by 10am PT on Friday, November 3rd
- Submit your answers to next week’s participation questions to Gradescope by 10am PT on Thursday, November 2nd
- Get started on your Q1 Project Checkpoint, due November 6th
- Replication Project Part 01: EDA
- Primary contact for replication project: Emily Ramond (eramond@deloitte.com) and cc: Nandita Rahman (nanrahman@deloitte.com)
- Office Hours: Tuesdays, 3:30-4:30pm PT