Abstract
A precise forecast in the energy sector is becoming increasingly essential and significantly contributes to meeting sustainability guidelines. In this hands-on workshop, you will work with a real dataset, develop features for a forecasting model, and evaluate their significance.
During the workshop, you will analyze historical data, identify key trends, and assess the relevance of features. Through interactive group exercises, you will develop new features and tackle practical challenges using anonymized datasets.
This workshop combines theory, practice, and collaboration to equip you with the tools and insights needed to succeed in energy demand and supply forecasting.
Objectives
– Enhance forecast accuracy through advanced feature engineering
– Identify trends and key variables for energy forecasting
– Understand the data-driven feature development process
– Apply tools to analyze feature importance
– Foster collaboration and hands-on problem-solving skills
Target Group
Data scientists
Prerequisites
Laptop, data science foundations and Python knowledge