All Courses AI

Intro to Machine Learning

Understand how machines learn from data. Train your first models, evaluate their performance, and apply ML to real problems using scikit-learn.

14 lessons ~3.5h Includes real project 100% Free
What You'll Build

Module 6 — Building Real ML Projects

Every course ends with a real project you build from scratch. No tutorials where you just follow along — you plan it, build it, and ship it yourself.

Course Curriculum

6 modules · 14 lessons · ~3.5h

1 Module 1 — How Machines Learn
3 lessons
  • What is Machine Learning? 12 min
  • Your First ML Model with scikit-learn 25 min
  • Features, Labels & Model Evaluation 18 min
2 Module 2 — Project: Predict Chicago Housing Prices
1 lessons
  • Project: Build a Predictive Model 10 min
3 Module 3 — Core ML Algorithms
3 lessons
  • Classification Algorithms 15 min
  • Model Evaluation 14 min
  • Clustering & Unsupervised Learning 13 min
4 Module 4 — Running ML Code Locally
2 lessons
  • Setting Up Your ML Environment in VS Code 16 min
  • Notebooks for Exploration, Scripts for Production 12 min
5 Module 5 — Supervised Learning in Depth
3 lessons
  • Linear Regression: Predicting Continuous Values 15 min
  • Decision Trees & Random Forests 15 min
  • Cross-Validation: Reliable Model Evaluation 12 min
6 Module 6 — Building Real ML Projects
2 lessons
  • Feature Engineering: Better Inputs, Better Models 15 min
  • Your First End-to-End ML Pipeline 20 min