Title: Overview
Course: Advanced Data Science: A Graduate Course > Section: Module 8: The RiverCity consulting engagement and defense

Module 8: The RiverCity consulting engagement and defense

Overview

The capstone is a single, defended, end-to-end project that mirrors real sponsored capstones such as those at the University of Chicago, Carnegie Mellon Heinz, and Harvard IACS, where students are retained by an external sponsor, work an ambiguous problem with messy data, and present to a review panel. Here you serve as a solo consultant to a recurring client, RiverCity, taking a genuine decision from a one-page brief through scoping, a leakage-safe build, an unannounced distribution-shift event that breaks your earlier models, a detection-and-adaptation cycle, and a live stakeholder defense. This module carries course outcome O7 (conduct and defend a complete, decision-facing data science engagement) and integrates everything from O1 through O6: framing and measurement, data acquisition and cleaning, valid evaluation, modeling, communication, and ethics and governance. Nothing here is a toy; the graded object is the record of fifteen weeks of decisions defended in real time before people who push back.

◆ Prepare and rehearse right here in the module. Your live meeting with the sponsor is still the graded defense.

The interactive simulation is the next item in this module. Open it there.

By the end of this module

- Run a full consulting engagement from an ambiguous one-page brief to a live defense, negotiating scope with a real point of contact and making the decision the client actually needs made.
- Design a leakage-safe, resampled evaluation whose reported uncertainty survives contact with new data.
- Detect, diagnose, and adapt to a distribution shift that quietly breaks a model already in service, using monitoring evidence rather than intuition.
- Deliver decision-maker-facing artifacts (an executive memo, a reproducible repository with a Model Card, and an explorable app) that a non-technical sponsor can act on.
- Defend your decisions live under adversarial but fair questioning from an executive, a compliance officer, and an engineer.

Tools and references

- Monitor for distribution shift with Evidently, an open-source library for data and model drift reports and test suites (Evidently) (link). Use it to produce the drift report you will submit as evidence.
- Ship an explorable app the client can open in a browser with Streamlit (link). Use it to let the sponsor test scenarios against your model without reading your code.

“Advanced Data Science by Michelle Blomberg is licensed under CC BY-NC-SA 4.0.”