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Free Sample - ML Practitioners Course

This is a complete sample module from the full 23-module program. It includes all 6 deliverables so you can experience the full teaching loop: Read → Explore → Quiz → Debug → Build.

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What's Inside This Sample

Module 5: "Decision Trees - 20 Questions for ML" - visual, intuitive, and showcases the interactive playground that makes this course unique.

• Micro-lesson (30–45 min) - How decision trees work, fail, and when to use them
• Interactive Playground - Watch the tree split in real time, drag thresholds, see overfitting happen
• Knowledge Check Quiz - Test your understanding of Gini, overfitting, and hyperparameters
• Debug Drill - Fix an overfit tree with 100% train accuracy and terrible test performance
• Practice Lab - Build a churn decision tree, visualize it, extract feature importances
• Cheatsheet - Quick reference with formulas, parameters, and code snippets

Why This Module?

Decision trees are visual and intuitive - perfect for appreciating the teaching quality without heavy prerequisites. The interactive HTML playground is a differentiator for this curriculum, and the debug drill targets something most practitioners haven't thought carefully about: when trees fail and why.

Start Here

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Module 5: Decision Trees - 20 Questions for ML

From Gini impurity to overfitting control, with an interactive playground where you can watch the tree learn in real time.

→ Start Module 5

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Want the full program?

The complete ML Practitioners Course includes 22 modules covering everything from Python foundations to agents and tool calling - each with interactive playgrounds, debug drills, and hands-on labs.

Email me at 189investmentai@gmail.com for details.

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Module 05: Decision Trees - 20 Questions for ML