Beginner 15 hours English Completion CertificateFREE
Editor's Pick
If you're starting from zero, this is the highest-quality free ML course available — it's literally what Google uses to train Googlers.
About this course
Machine Learning Crash Course (MLCC) is Google's own internal ML primer, opened up to the public for free. It's built around short video lessons paired with interactive coding exercises in Colab notebooks, rather than long-form lectures — you read a concept, then immediately apply it in a live notebook. The course covers the standard supervised-learning foundation: linear and logistic regression, classification, neural networks, and an applied module on real-world ML problems like fairness and production considerations.
What distinguishes MLCC from typical free intro courses is its emphasis on practical engineering judgment over theory. Google updates it periodically to reflect current best practice, and the most recent version folds in a module specifically on large language models. There's no certificate, but the content quality and zero cost make it a near-mandatory first stop for anyone exploring ML seriously, often used alongside or before paid specializations like DeepLearning.AI's.
What you'll learn
Understand core ML concepts: loss functions, gradient descent, and overfitting
Build and evaluate linear and logistic regression models
Understand the basics of neural networks and when to use them
Work hands-on with TensorFlow in Colab notebooks
Recognize common pitfalls: data bias, overfitting, and fairness issues
Apply ML thinking to real-world production problems
This course includes
15h
On-demand video
Yes
Mobile access
English
Language
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Instructor
GA
Google AI Education Team
Google instructor
3M+ learners20 courses4.7 instructor rating
Developed and maintained by Google's AI Education team, drawing on internal training material Google uses to onboard its own engineers into applied machine learning.
Requirements
Basic Python programming ability
High-school-level algebra; no calculus required to start
A Google account for running Colab notebooks (free)
Who this course is for
Complete beginners to machine learning who want a rigorous but free start
Software engineers adding ML to their skill set
Anyone evaluating whether to invest in a paid ML specialization next
About this provider
GO
Google
Free, self-paced courses and certificates from Google — Career Certificates, Digital Garage, and Machine Learning Crash Course.
Yes, completely free with no paywall, audit limit, or certificate upsell. It's the same material Google uses internally; they've simply made it public.
No. MLCC doesn't offer a certificate — it's positioned as a learning resource, not a credential. If you need a certificate for a resume, pair it with a Coursera specialization like DeepLearning.AI's Machine Learning Specialization.
Roughly 15 hours of core content, though most learners spend longer working through the interactive exercises carefully. It's self-paced with no deadline.
No — MLCC is a strong foundation, not a job-ready credential. Most learners follow it with a more in-depth specialization (Andrew Ng's courses, fast.ai, or a formal degree program) and build a portfolio of projects.
It introduces neural network basics and includes an LLM module, but deep learning in depth (CNNs, transformers at scale) is better covered by DeepLearning.AI's Deep Learning Specialization.