Foundational courses

The foundational courses cover machine learning fundamentals and core concepts.

We recommend taking them in the order below.

Introduction to Machine Learning

A brief introduction to machine learning.
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Machine Learning Crash Course

A hands-on course to explore the critical basics of machine learning.

Problem Framing

A course to help you map real-world problems to machine learning solutions.
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Managing ML Projects

Learn how to manage machine learning projects.

Advanced courses

The advanced courses teach tools and techniques for solving a variety of machine learning problems.

The courses are structured independently. Take them based on interest or problem domain.

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Decision Forests

Decision forests are an alternative to neural networks.

Recommendation Systems

Recommendation systems generate personalized suggestions.

Clustering

Clustering is a key unsupervised machine learning strategy to associate related items.

Generative Adversarial Networks

GANs create new data instances that resemble your training data.

Guides

Our guides offer simple step-by-step walkthroughs for solving common machine learning problems using best practices.

Rules of ML

Become a better machine learning engineer by following these machine learning best practices used at Google.

People + AI Guidebook

This guide assists UXers, PMs, and developers in collaboratively working through AI design topics and questions.

Text Classification

This comprehensive guide provides a walkthrough to solving text classification problems using machine learning.

Good Data Analysis

This guide describes the tricks that an expert data analyst uses to evaluate huge data sets in machine learning problems.

Deep Learning Tuning Playbook

This guide explains a scientific way to optimize the training of deep learning models.

Data Traps

This guide presents common mistakes that ML practitioners might encounter when working with data and statistics.

Intro to Responsible AI

This beginner guide gives an overview of how to build fairness, accountability, safety, and privacy into AI systems.

Adversarial Testing for Generative AI

Walk through an example adversarial testing workflow.

Glossaries

The glossaries define machine learning terms.
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Fundamentals of machine learning

ML fundamental terms and definitions.
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Decision forest

Decision forest key terms and definitions.
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Clustering

Clustering key terms and definitions.

Full glossary

Full glossary containing all definitions.