Data Analytics for Power Engineering: Course Guide

Brief overview

This course helps students master modern approaches to data analysis and understand how numerical measurements, tables, time series and images can yield useful engineering insights.

Course structure

The learning sequence progresses from basic data principles to processing, visualisation and analysis.

Key topics include:

– preparing and cleaning data;

– working with tables and datasets;

– time-series analysis;

– visualising results;

– identifying patterns;

– interpreting data for applied tasks;

– preparing data for subsequent AI and machine-learning methods.

Distinctive features

The course's main feature is its direct connection to practical power engineering tasks.

Students learn to see beyond charts and tables to equipment condition, power system operating regimes, possible anomalies, trends and the evidence needed for engineering decisions.

Why do future specialists need this?

Modern digital energy solutions—forecasting, diagnostics, monitoring, digital models and intelligent decision support—all depend on data analysis.

Data Analytics Technologies provides the foundation for advancing to machine learning, AI models and digital tools for electric power engineering.