The project aims to develop a predictive financial investment model for real estate, focusing on estimating the future value of properties based on investors' goals. The model will integrate historical data of investment properties with macroeconomic indicators, county-specific insights, investment rates, and loan types. By analyzing these factors, the model will provide a comprehensive understanding of how various elements influence property values over time. This project offers learners the opportunity to apply their knowledge of data analysis, financial modeling, and economic principles to a real-world scenario. The goal is to create a tool that can assist investors in making informed decisions by predicting property values at specific future points.

The primary deliverable is a functional predictive model that estimates real estate investment values. Additional deliverables include a detailed report explaining the model's methodology, data sources, and assumptions. The model will have a UX component for input values and an output UX with projected values, along with the actual model (Python, etc.). The team will also provide a presentation summarizing the project's findings and potential applications. The deliverables will demonstrate the learners' ability to synthesize classroom knowledge into practical financial modeling solutions.