The race to net-zero emissions is heating up. As nations work to combat climate change and meet rising energy demands, renewable energy has emerged as a cornerstone of the clean transition. Solar, wind, and hydro are revolutionizing how we power our lives. Some countries are leading the charge, while others are falling behind. But which nations are making the biggest impact? What’s driving their success? And what lessons can we learn to accelerate green energy transition? As a data scientist at NextEra Energy, one of the world’s leading renewable energy providers, your role is to move beyond exploration, into prediction. Using a rich, real-world dataset, you’ll build models to forecast renewable energy production, drawing on indicators like GDP, population, carbon emissions, and policy metrics. With the world watching, your model could help shape smarter investments, forward-thinking policies, and a faster transition to clean energy. 🔮⚡🌱 As a data scientist at NextEra Energy, your task is to use the Training Set (80% of the data) to train a powerful machine learning model that can predict renewable energy production (GWh). Once your model is trained, you will use it to generate predictions for the Test Set, which does not include the target (`Production (GWh)`) but has an additional `ID` column. Your task: Scoring notes: Your submission will be evaluated based on Model accuracy (80%), measured by RMSE, and Community Votes (20%).