Machine Learning Crash Course
Google’s free introduction to how machine learning works, from regression and classification to neural networks, embeddings, LLMs, and production systems. It assumes no ML knowledge, but Google recommends Python, NumPy, pandas, and comfort with algebra and basic statistics.
Go to the course on Google- Provider
- Price
- Free
- Certificate
- Free badgeNo formal certificate; score 80% on a module’s final quiz to earn that module’s badge (Google ML Education Help Center).
- Level
- All levels
- Time
- Google’s module estimates add up to about 13.5 hours (its 2024 announcement said 15 hours)
- Format
- 12 self-paced modules with animated videos, interactive visualizations, quizzes, and Colab programming exercises
- Checked
- 2026-11-05
Free to read online. No Google account is needed for the lessons, but the Colab programming exercises need one.
01
What you will learn.
- 01Linear and logistic regression
- 02Working with data
- 03Neural networks
- 04Embeddings
- 05Intro to LLMs
- 06ML fairness
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02
Before you enroll.
From the course page, checked 2026-11-05.
- Who it is for
- Technically minded people who are new to machine learning or want a refresher.
- You need
- Intro algebra and basic statistics: linear equations, mean, histograms
- Programming experience, ideally Python, for the exercises
- NumPy and pandas basics (Google links quick Colab tutorials)
- A Google account for the Colab exercises
- What you build
- Colab exercises on linear regression, classification, data cleaning, and fairness
- Good to know
- Not a tutorial on ML APIs such as Keras
03
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