Intermediate Machine Learning: Advanced Models on Real Market Data

You have built your first machine learning model. Now it is time to make it better. This course picks up where the intro left off, using the same Nairobi rental market data but going deeper. You will learn the techniques that separate a basic model from one that can actually perform in production.

By the end of this course you will have:

1. Learned how to handle missing values properly instead of just dropping them
2. Encoded categorical variables so your model can use location and property type
3. Built cleaner workflows using pipelines
4. Validated your model properly using cross validation
5. Implemented XGBoost, one of the most powerful models in data science
6. Understood data leakage and why it silently destroys models

Basic Python and completion of the intro course or equivalent knowledge is required. If you have not taken the intro course, consider the bundle for a discounted price on both. Everything runs offline on your own machine with no subscriptions, no cloud setup, and no hidden costs. This is not a course about theory. It is about doing the work.