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Reveal House Sale Price Secrets Using Machine Learning

BeginnerGuided Project

Embark on an exciting journey into Real Estate with Machine Learning and AI! We'll guide you how to predict house prices, a fundamental task in real estate analytics. You'll gain hands-on expertise using advanced techniques like SHAP (SHapley Additive exPlanations) and Random Forest, empowering you to interpret model results effectively. Whether you're a novice or have some background in data analysis, this project will equip you with the skills needed to excel in your career and confidently apply AI and ML in your job.

4.6 (32 Reviews)

Language

  • English

Topic

  • Machine Learning

Industries

  • Real Estate, Investment

Enrollment Count

  • 252

Skills You Will Learn

  • Artificial Intelligence, Machine Learning, Python

Offered By

  • IBMSkillsNetwork

Estimated Effort

  • 30 minutes

Platform

  • SkillsNetwork

Last Update

  • October 17, 2025
About this Guided Project
Are you ready to revolutionize your career in real estate? Imagine having the power to predict property prices, make informed investment decisions, and gain an edge in this competitive field. With the advent of Machine Learning and AI, these dreams can become a reality.

Welcome to our exciting project that will take you on a journey through the dynamic world of real estate using cutting-edge technology. Whether you're just starting your career in the industry or looking to enhance your existing skills, this project is tailor-made for you.


A Look at the Project Ahead

Picture this: You're a real estate agent armed with the ability to predict house prices accurately, helping your clients make informed decisions about buying or selling property. Imagine being a property investor with the capability to identify lucrative opportunities before they even hit the market. The possibilities are endless, and the future of real estate belongs to those who can harness the power of AI and Machine Learning.
Source: DALL.E
In this project, you will wear the hat of a professional real estate analyst and data scientist as you dive into the realm of housing market predictions. Your mission is to create a robust predictive model that can accurately estimate the selling price of houses. But it doesn't stop there; you'll also use the powerful SHAP (SHapley Additive exPlanations) library to dissect your model and identify which factors of the house have the most significant impact on house prices.


By taking on this project, you'll gain a multitude of skills and insights that will be valuable in your data science journey:
  • Mastery of Random Forest regression modeling.
  • Proficiency in feature engineering and preprocessing.
  • Interpretation of SHAP values for model explanation.
  • Data visualization and storytelling through interactive dashboards.
  • Real-world applications of machine learning in the real estate sector.
  • Improved Python programming skills.
  • Practical experience in handling and analyzing real-world datasets.

What You'll Need

  • Your passion and interest.
  • Basic knowledge of Python programming.

Instructors

Kang Wang

Data Scientist

I was a Data Scientist in the IBM. I also hold a PhD from the University of Waterloo.

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Contributors

Joseph Santarcangelo

Senior Data Scientist at IBM

Joseph has a Ph.D. in Electrical Engineering, his research focused on using machine learning, signal processing, and computer vision to determine how videos impact human cognition. Joseph has been working for IBM since he completed his PhD.

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Wojciech "Victor" Fulmyk

Data Scientist at IBM

I am a data scientist and economist with a strong background in econometrics, time series analysis, causal inference, and statistics. I stand out for my ability to combine technical expertise with clear communication, turning complex data findings into practical insights for stakeholders at every level. Follow my projects to learn about data science principles, machine learning algorithms, and artificial intelligence agents.

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