UNIT 016 h allocated
Time-aware data
- Seasonality
- autocorrelation
- missing intervals
- resampling
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MACHINE LEARNING / SPECIALIST
ML240Time-series forecasting & anomaly detection
24 h productive allocation9 h 36 m learning + 14 h 24 m training4 units · 1 assessed practical brief
Detailed course plan and training brief. A complete taught course pack is in preparation. The linked foundation module, where shown, is a smaller available resource.
BEFORE YOU BEGIN
A clear starting point.
Specialist studio; environment and faculty must be confirmed before scheduling
WHAT YOU SHOULD BE ABLE TO DEMONSTRATE
- Explain the assumptions and failure modes in time-aware data.
- Complete the practical: compare persistence, a feature-based model and a sequence approach using rolling-origin evaluation.
- Defend the resulting forecast notebook with reproducible evidence.
THE SUBJECTS / FOUR CONNECTED UNITS
What you will study.
UNIT 026 h allocated
Forecast baselines
- Persistence
- seasonal naive
- rolling features
- prediction horizons
UNIT 036 h allocated
Temporal models
- Statistical forecasts
- boosted models
- sequence networks
- covariates
UNIT 046 h allocated
Backtesting
- Rolling origins
- leakage
- interval coverage
- drift and anomalies
THE TRAINING STUDIO
Make the subject
visible in your work.
Compare persistence, a feature-based model and a sequence approach using rolling-origin evaluation.
Evidence to produce
- Forecast notebook
- horizon-wise errors
- uncertainty report
Training brief for supervised delivery. Code, datasets, answer keys and environment acceptance must be completed in the full course pack before delivery is confirmed.
ASSESS THE REASONING
A question you
should be able to answer.
Why can a random train-test split inflate forecasting performance?
Review dimensions
Technical correctness · reproducibility · interpretation of results · failure analysis · individual explanation. Course-level rubric and faculty moderation form part of the final adopted teaching pack.
External reference access, hardware, cloud accounts and paid services are separate. No third-party certification is included by implication.