# Machine Learning Crash Course Source: https://freeaicourses.com/courses/machine-learning-crash-course Last checked: 2026-10-04 (module list and timings, prerequisites, prework, tools, badges and free access) ## Short answer Our Google Machine Learning Crash Course review: it is the best free machine learning course for people who can already program. Google teaches 12 modules in about 13.5 hours with animated videos, interactive visualisations and Colab exercises. Nothing is behind a paywall, but you earn quiz badges, not a certificate. ## Key facts - Provider: Google - Time to complete: About 13.5 hours by Google's module timings, not counting prework - Modules: 12, of 30 to 110 minutes each - Prework: Introduction to Machine Learning, NumPy UltraQuick Tutorial, pandas UltraQuick Tutorial - Credential: A badge for each module quiz, no certificate - Exercises: Colab in the browser, no setup, using NumPy, pandas and Keras - Running since: 2018 ## Who it is for - Programmers, ideally in Python, who want the core machine learning ideas to stick - Learners who finished Kaggle Intro to Machine Learning and want more depth - Anyone who wants a module on large language models alongside the classic topics ## Who should skip it - Anyone who needs a certificate: Google gives quiz badges, not a certificate - Anyone who has not programmed yet: take Kaggle Learn: Python first - Learners who want machine learning APIs taught in depth: Google says the course does not do that ## What you can do afterwards - Explain linear regression and logistic regression, and how classification works - Prepare numerical and categorical data for a model - Spot overfitting and explain why datasets and generalisation matter - Describe neural networks, embeddings and large language models - Weigh production systems, automated machine learning and fairness ## What the course covers - Linear regression: Google lists this module at 80 minutes. - Logistic regression: Google lists this module at 35 minutes. - Classification: Google lists this module at 70 minutes. - Working with numerical data: Google lists this module at 85 minutes. - Working with categorical data: Google lists this module at 50 minutes. - Datasets, generalization, and overfitting: Google lists this module at 105 minutes, the second longest. - Neural networks: Google lists this module at 75 minutes. - Embeddings: Google lists this module at 45 minutes. - Large language models: Google lists this module at 45 minutes. - Production ML systems: Google lists this module at 80 minutes. - Automated machine learning: Google lists this module at 30 minutes, the shortest. - Fairness: Google lists this module at 110 minutes, the longest. ## What works - Nothing is behind a paywall: all the pages are open on developers.google.com - Animated videos, interactive visualisations and practice exercises in one course - Exercises run in Colab in your browser with no setup - The modules are self-contained, with Google's own minutes shown for each - Google has run it since 2018, and the refreshed version covers recent advances, including a large language models module ## What does not - There is no certificate: each module's quiz earns a badge and that is all - It is not a first course: Google lists prerequisites and says you should be a good programmer - The prework is extra: Google's Introduction to Machine Learning course and the NumPy and pandas UltraQuick tutorials - Google says it does not teach machine learning APIs in depth - Some modules are long: Fairness is 110 minutes and Datasets, generalization, and overfitting is 105 ## The catch There is no certificate: each module's quiz earns a badge, and that is the only credential. It is also not a first course. Google lists prerequisites and prework (its Introduction to Machine Learning course, a NumPy tutorial and a pandas tutorial) that are not in the 13.5 hours. If that is too much, take Kaggle Intro to Machine Learning first: it is 3 hours and gets you to a working model. ## Is it still current? Google describes a refreshed version that covers recent advances in AI, and it now includes a 45 minute Large language models module. The course has run since 2018, and Google's pages were checked on 4 October 2026. ## Take before Kaggle Intro to Machine Learning ## Take after - CS50's Introduction to AI with Python - AI for Beginners ## Verdict Take Machine Learning Crash Course if you can already program and want the ideas explained properly. It scores 8.5: hands-on is 8 because the exercises run in Colab, depth is 7 because 12 modules run from linear regression to fairness, and truly free is 10 because every page is open. It is not a first course: Google expects you to be comfortable with variables, linear equations, graphs of functions, histograms and means, and says you should be a good programmer. ## Questions people ask ### Is Google's Machine Learning Crash Course free? Yes. All the pages are open on developers.google.com, and the exercises run in Colab in your browser with no setup. ### Does Machine Learning Crash Course give a certificate? No. Each module's quiz earns a badge, for example the Linear Regression badge, but Google does not offer a certificate. ### How long is Machine Learning Crash Course? About 13.5 hours by Google's own module timings, which add up to 810 minutes across 12 modules. That does not count the prework, so plan for more. ### What do I need before Machine Learning Crash Course? Google asks you to be comfortable with variables, linear equations, graphs of functions, histograms and statistical means. It says you should be a good programmer, ideally in Python. Calculus is optional. If that sounds like a stretch, Kaggle Learn: Python and Kaggle Intro to Machine Learning are the gentler route in. ### Do I have to take the modules in order? No, each module is self-contained. Google recommends that anyone new to machine learning completes them in the order listed: from Linear regression through to Fairness. If you already know the basics, you can jump to a single module, such as Large language models at 45 minutes. ### What is the prework for Machine Learning Crash Course? Google lists its Introduction to Machine Learning course, the NumPy UltraQuick Tutorial and the pandas UltraQuick Tutorial. 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