Earlybuild GmbH is seeking to enhance its capabilities in predicting rental prices using advanced data analytics. The goal of this project is to develop a predictive model that accurately forecasts rental prices based on historical data and relevant market indicators. This project will allow learners to apply their knowledge of data analytics, machine learning, and statistical modeling. The team will work with a dataset provided by Earlybuild GmbH, which includes historical rental prices, property features, and economic indicators. The project will involve data cleaning, exploratory data analysis, feature engineering, model selection, and evaluation. The learners will gain hands-on experience in applying classroom knowledge to a real-world problem, enhancing their skills in data-driven decision-making.

The project deliverables include a comprehensive report and a functional predictive model. The report should detail the data preprocessing steps, exploratory data analysis, feature selection, and model evaluation metrics. Additionally, the team will deliver a presentation summarizing their findings and recommendations. The predictive model should be implemented in a programming language such as Python or R and be accompanied by clear documentation.