Overview
What this challenge is about.
Build 14-day DAU forecasts per region with SARIMA and gradient-boosted models, then deliver a Streamlit dashboard and evaluation report for a verifiable certificate.
The scenario
The Vancouver studio (around USD 240M revenue, live-ops drive 70 percent of monthly revenue) cannot afford to mis-time content drops — every week off the optimal window costs around USD 600k in monetization.
The Brief
What you'll do, and what you'll demonstrate.
Forecast DAU 14 days ahead per region with MAPE beating the finance-team spreadsheet baseline.
Earning criteria — what you'll demonstrate
- Apply both classical and ML approaches to time-series forecasting
- Use rolling-origin cross-validation for honest forecast evaluation
- Engineer time-aware features (lags, calendar effects, event indicators)
- Operationalize forecasts for live-ops decision-making
Program Fit
Where this fits in your program.
Sharpens the same skills your degree expects you to demonstrate.
Machine Learning (CS Elective)
Master · General Studies
Strong alignment
This challenge maps to Machine Learning (CS Elective) at the Master level. It sharpens the same practical skills your coursework expects — but in a real industry context with actual constraints and deliverables.
Skills
Skills you'll demonstrate.
Each one shows up on your verified credential.
- Supervised Learning
Apply supervised learning to solve real industry problems and demonstrate production-level capability.
- Time Series Forecasting
Apply time series forecasting to solve real industry problems and demonstrate production-level capability.
- Python Programming
Apply python programming to solve real industry problems and demonstrate production-level capability.
- Ml Applications
Apply ml applications to solve real industry problems and demonstrate production-level capability.
- Model Evaluation
Apply model evaluation to solve real industry problems and demonstrate production-level capability.
- Business Analytics
Apply business analytics to solve real industry problems and demonstrate production-level capability.
Careers
Career paths this challenge builds toward
Completing this challenge demonstrates skills that transfer directly to these roles:
Product Manager
PMs on live-ops products need forecasting fluency to time content drops and marketing pushes without burning revenue windows.
This challenge sharpens
- business-analytics
- time-series-forecasting
- model-evaluation