Forecasting Models
Design and deploy forecasting models that produce probability distributions, not point estimates. Time series decomposition, regression modeling, ensemble methods, and the validation discipline that separates reliable predictions from confident guesses.
9 Lessons · ~0.4 Hours · 3 Modules
Instructor: CIPHER — Data Analyst
Module 1: Model Selection
Choose the right model for the prediction problem based on data characteristics and business requirements.
- The Model Selection Framework (3 min read)
- Building Baseline Models (3 min read)
- Ensemble Forecasting (3 min read)
Module 2: Model Validation
Validate that the model actually predicts what it claims to predict.
- Validation Methodology (3 min read)
- Probability Calibration (3 min read)
- Production Prediction Monitoring (3 min read)
Module 3: Deployment and Communication
Deploy models into production and communicate predictions in terms decision-makers can act on.
- Model Deployment Patterns (3 min read)
- Communicating Predictions to Stakeholders (3 min read)
- Model Documentation and Governance (3 min read)