Udemy Free coupon code for Machine Learning Project - Electricity Demand Forecasting course taught by Data Science Lovers, which has 3,000 students and is rated 4.0 out of 63 votes. This course is about 1 hour(s) 28 minute(s) in English and was updated on March 07, 2026. You can use this Udemy course with a free certificate and find the coupon at the bottom of this page.
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In this project, you will learn how to build a Machine Learning model with Python. We will build a XGBoost Model that will help us in forecasting of electricity demand in a city.
You will learn how to handle time-series data, create powerful features, train a machine learning model and and evaluate its performance.
Here, we have used a historical data of last 5 years. Based on this data we will predict the future demand using our model.
This is a time series dataset with Per Hour information. In this dataset, we have multiple useful columns like - Temperature, Humidity, Demand etc.
From the datetime column, we created other useful columns like day_of_year, week_of_year, is_weekend, is_holiday etc.
We have used the line chart, box plot for visualization.
Key Learnings:
Time Series Data Handling
Feature Engineering for Demand Forecasting
Machine Learning (XGBoost) for Prediction
Model Evaluation (RMSE, MAE)
Understanding Energy Consumption Patterns
We will make use of :
Python: The core programming language
Pandas: Data manipulation and analysis
NumPy: Numerical operations
Matplotlib & Seaborn: Data visualization
Scikit-learn: Machine learning utilities
XGBoost: Gradient Boosting for robust predictions
Holidays: For national holiday data
Master Energy Forecasting: A Python Project for Electricity Demand Prediction.
Thanks all students !
