ProfessionalIntermediate
AI Applications in Power Systems
Apply machine learning to load forecasting, fault detection and grid optimisation with practical Python labs.
Program Overview
Engineers learn to frame power-system problems as ML tasks, prepare data, train models for forecasting and anomaly detection, and responsibly deploy them into operational workflows.
What you will learn
- Frame power problems as ML tasks
- Build load-forecasting models
- Detect faults & anomalies with ML
- Evaluate and validate models
- Understand MLOps for utilities
Curriculum highlights
01Data preparation for grids
02Time-series forecasting
03Anomaly detection
04Model evaluation
05Deployment & monitoring
Upcoming sessions
2 November 2026
20 of 20 seats available8 February 2027
20 of 20 seats availableSeats are confirmed on a first-come, first-served basis.