Before coding, we plan — and in this screencast, I walk through the concept, tools, duration, and first AI-assisted prompt for the project.
We’re building a two-step real estate investment analysis tool designed to help identify and rank investment opportunities based on rental income and expenses.
What the tool will do:
🏡 Step 1 – Screening: Read MLS sales and rental data, estimate mortgage payments, match rentals, and flag properties that hit a target profit.
💵 Step 2 – Finalization: Once expenses (taxes, HOA, insurance, MI) are added, calculate full PITI and Net Profit to rank results.
In this video:
1️⃣ I describe the project concept and goals.
2️⃣ I outline the tools we’ll need — Python 3.11+, Pandas, NumPy, and your own sales/rental CSVs.
3️⃣ I share the expected duration and workflow for the build.
4️⃣ I demonstrate how to write and paste your first prompt into ChatGPT to generate a custom project outline — showing how to engage AI as a learning partner through the AAEL framework.
The next screencast (Module 1) begins the hands-on work: data cleaning, refining the AI outline, and writing our first Python script.