Practical AI for Real Estate

4 x 2h live online classes  

Next course start: 2nd June 2025

4 sessions: 2nd, 6th, 9th & 13th of June 20253pm - 5pm (UK time)

World-class faculty

Manageable format 4x2h 3pm-5pm (UK time)

Fully practical - leave ready to use AI

Delivered by experts from University College London

Tailored to real estate professionals

Practical AI for real estate - course description

The course is an essential primer on generative AI for real estate professionals. It covers the basics of what AI is and how to use it in an accessible way tailored to the real estate industry. It requires no technical knowledge or AI skills.

It covers knowledge and skills everyone in real estate needs to have to stay competitive in an AI-powered world. 

We use experiential learning techniques that are both engaging and effective in delivering applicable knowledge fast.

The course is extremely practical and features multiple cases studies designed by a team of world-leading academics from University College London (ranked #1 in the world for Built Environment) specifically for this course.


Each case study demonstrates an application of state-of-art, research-based use of AI techniques to solve a very relatable problem.

All uses cases we present have been developed in-house by academics collaborating with industry experts and include:


ON COMPLETION OF THIS COURSE YOU WILL:

Understand the fundamentals of AI and Machine Learning and their application in real estate.

Have the skills to apply AI for real estate market research, strategy and risk analysis and data visualisation.

Understand ethical considerations of using AI in real estate.                    

Know the advantages and potential pitfalls of AI implementation in real estate.

COURSE CONTENT:

SEE BROCHURE FOR DETAILS

Each session consists of of a short theoretical introduction followed by a  practical workshop lead by subject area experts. 

Session 1: Theory (introduction to how AI works) + application (strategy & analysis)

Session 2: Theory (hallucinations, agents & RAG) + application (market research with AI)

Session 3: Theory (code & visualisations) + application (data analysis & visualisation)

Session 4: Theory (ethics & security) + application (adoption, use cases & outlook)

As presented at: