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Module
Module 3 of 5Lesson 1 of 3~12 min

Master the indicators before handing them to AI

To judge a spreadsheet produced by AI, you must know how to redo the math on your own. This lesson works through the key indicators of a rental investment by hand, from yield to cash flow, and explains the convention behind each. You can then catch a wrong figure before it reaches a client.

Take this lesson: your first course is freeSee the full syllabus

Lesson objective

By the end of this lesson, you will be able to calculate by hand the total cost, gross yield, net yield after charges, monthly repayment and cash flow of a buy-to-let investment, and explain the convention used for each.

Topics covered

  • rental yield
  • real estate cash flow
  • net return
  • mortgage payment

Where it fits

Model a reliable rental yield

How do I build, with AI, a yield model I can actually use to make decisions?

Lessons in this module

  1. Master the indicators before handing them to AI (this lesson)
  2. Have AI build a yield spreadsheet, then check it
  3. Check tax and regulations without delegating the advice

What you will learn in the course

This lesson is part of the course AI for real estate professionals (France)

  • Identify the tasks in your work to hand to AI and the points where human checking is mandatory.
  • Prepare client data in line with the GDPR before any AI processing (minimize, pseudonymize or anonymize, choose the tool and plan).
  • Build a rental yield spreadsheet with AI (gross yield, net yield, cash flow, three scenarios) and check its formulas against a case worked out by hand.
  • Check a tax or regulatory claim produced by AI against a dated official source, and recognize when to consult a professional.
  • Write a listing with AI that includes the mandatory notices and no unverifiable claim.
  • Produce a reasoned valuation range from DVF comparables given to the AI, and qualify a lead with an explicit grid, explaining the limits of each result.
  • Specify a field prospecting app, validate it in a spreadsheet, then prototype it without code, listing what is missing for production use.

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