Clean Energy Consumption Forecasting Project

What is the main goal for this project?
The goal of this project is to create a forecasting system using Regression Supervised Machine Learning to predict Clean Energy consumption. This will involve several steps including but not limited to:

• Analyzing existing datasets of clean energy consumption.
• Developing a forecasting model using regression supervised learning.
• Optimizing the model's accuracy and assessing areas for improvement.
• Researching other variables that can improve the accuracy of the model.
• Accounting for additional variables in the forecasting model.
• Testing the developed model and making improvements based on additional data.

DUTIES AND RESPONSIBILITIES
By the end of the project:

• Understanding of existing datasets of clean energy consumption.
• Understanding of variables that affect the accuracy of the forecasting model.
• Identification of areas for future improvement of the model.
• Testing the developed model with real-world data and accounting for additional parameters.

Final deliverables should include:

• All source code.
• A written report explaining the design process and outcomes.

SKILLS TO BE DEVELOPED
As part of doing this project, interns can expect to be upskilled on below:

• Regression Supervised Machine Learning and Data Analysis.
• Python, Machine learning.