Step 1
Learn the basics of ML
Learning path
ML Foundations
Understand the key ideas behind ML, data patterns, and small practical experiments.
Your learning steps
Step 2
Understand data and patterns
Step 3
Try a notebook
Step 4
Practice with examples
Recommended tools
Python
A practical language for coding, automation, and data-focused beginner learning.
Google Colab
An easy environment for notebooks, data analysis, and beginner ML experiments.
Kaggle
A beginner-friendly place to learn from datasets, notebooks, and real examples.
Starter packs for this path
ML Foundations Workbook
A beginner-friendly workbook for ML concepts, data thinking, and small experiments.