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Activity 5
AI to Predict House Prices

How does an AI predict house prices?

AIs learn from historical data. An AI that has analyzed the historical prices of a neighborhood-based on information such as square footage, age etc can be used to predict the price of any house in the neighborhood based on the same characteristics/features such as square footage, age etc.

Let's collect the data needed to build the AI

  • In this activity, students will build an AI by collecting data from a real estate website called Redfin. They can choose the neighborhood they want to collect the data from.

  • Students also have the option to download data from public repositories (a) Option 1 
    (b) Option 2

  • Goal of this activity is to build a regression AI.

This video shows how data can be downloaded from a neighborhood of your choice. You can demonstrate this live in the class.

Let's build an AI to predict house prices

We will use the dataset we collected to build a regression AI.

Open Navigator

​​How to start using Navigator

1. Go to

2. Follow the instructions in the video below to build the AI

(If you are enrolled in an AIClub course:

To open the Navigator console, login to your AIClub account. Click on your profile icon on the top right corner and select Go to Navigator from the dropdown.)

Observe and Discuss


1. Do you think the AI is doing a good job at predicting the prices of houses?

2. Which feature in the dataset has maximum impact on price?

3. Can you quantify how good or bad the AI is?

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