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Analysis

Forecast Daily Demand for an Apparel Supply-Chain Team

FreeVerified credential2 weeksIntermediate

Overview

What this challenge is about.

You receive 24 months of daily sales for 500 SKUs across 200 stores, plus calendar features (holidays, promotions, weather codes). Forecast 14 days out per SKU-store. Benchmark SARIMA, LightGBM (with lag + calendar features), and a small N-BEATS or Temporal Fusion Transformer (TFT) on a rolling-origin evaluation. Report Mean Absolute Scaled Error (MASE) and bias by horizon. Deliver the benchmark notebook, a results table, and a 3-page recommendation memo.

CredentialBlockchain-anchored
ShareableLinkedIn-ready
LanguageEnglish
PaceSelf-paced

The Brief

What you'll do, and what you'll demonstrate.

Pick the demand-forecasting approach that gives the best MASE improvement over the SARIMA baseline at acceptable training cost.

Earning criteria — what you'll demonstrate

  • Apply SARIMA, tree-based, and neural forecasters to real retail data
  • Evaluate forecasts with rolling-origin folds (not random split)
  • Quantify bias and error by forecast horizon
  • Communicate a forecasting recommendation to a supply-chain audience

Program Fit

Where this fits in your program.

Sharpens the same skills your degree expects you to demonstrate.

Careers

Roles this prepares you for.

Real titles. Real skill bridges. Pick the one closest to your trajectory.

Career paths this builds toward

Canonical roles

Data Scientist

Forecasting at SKU-store scale with rigorous rolling evaluation is the textbook senior data-scientist project at any large retailer.

This challenge sharpens

  • time-series-forecasting
  • rolling-evaluation
  • sarima

Machine Learning Engineer

Comparing classical, tree-based, and neural forecasters across cost and accuracy is the same trade-off MLEs make for production deployment.

This challenge sharpens

  • gradient-boosting
  • neural-forecasting
  • rolling-evaluation

Applied AI Scientist

Translating forecast error analysis into a supply-chain memo is the bread and butter of applied-AI work in operations-heavy retail.

This challenge sharpens

  • time-series-forecasting
  • neural-forecasting
  • sarima

One more thing

You can put a credential on your CV by Friday.