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AI and machine learning courses

7 courses that build on each other, from your first line of Python to deep learning and generative AI. Every course is free to start.

Start with Python Follow the machine learning path

174 lessons open · 317 in the syllabus · 675 quiz questions

Foundations

The programming, data handling, maths and statistics every model is built on.

  1. Python for AI and Machine Learning

    From your first line of code to tested, readable Python for data work.

    Beginner7 modules · 33 lessonsNeeds: None. Start here if you have never programmed

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  2. Data Tools: NumPy, pandas, Matplotlib and scikit-learn

    NumPy, pandas and charts, with every shape and join predictable.

    Beginner5 modules · 23 lessonsNeeds: Basic Python

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  3. Maths for Machine Learning

    The algebra, vectors and calculus that training a model uses.

    Beginner6 modules · 26 lessonsNeeds: School algebra

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  4. Statistics and Probability for Machine Learning

    Probability, inference and experiments, read the honest way.

    Beginner8 modules · 41 lessonsNeeds: School algebra and basic Python

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Machine learning

Every classical model, built from scratch, then with scikit-learn, on real data.

  1. Practical Machine Learning in Python

    Regression to ensembles, clustering and time series, built from scratch.

    Beginner18 modules · 51 of 91 lessons openNeeds: Basic Python; the maths each lesson needs is linked from itLessons being added

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Deep learning and generative AI

Neural networks and transformers in PyTorch, then large language models, RAG and agents.

  1. Deep Learning with PyTorch

    Neural networks, CNNs and transformers in PyTorch, taken to deployment.

    Intermediate11 modules · 49 lessons plannedNeeds: Machine Learning up to linear classifiersNew

    See the syllabus

  2. Generative AI: LLMs, RAG and Agents

    LLMs, post-training, RAG, tools and agents, fine-tuning and diffusion.

    Advanced13 modules · 54 lessons plannedNeeds: Deep Learning Modules 0 to 6New

    See the syllabus

Questions about the courses

Which course should I start with?

Any course you like. Each one lists what it needs first, and every lesson links to the earlier lessons it builds on. If you are new to programming, start with Python; if you want a guided order, follow the machine learning path.

Do I have to finish the maths before machine learning?

No. Each machine learning lesson links to the maths and statistics it uses, and the machine learning path places each of those lessons just before the model that needs it.

What is free?

Every published lesson, its key terms and every free video, with no account. A free account opens each lesson's quiz, saves your progress, and opens every layer of the free sample modules. Pro adds the practice, notebooks, projects, certificates and live sessions everywhere.

Do the courses cover deep learning, LLMs and agents?

Yes. Deep Learning teaches neural networks, CNNs, transformers and deployment in PyTorch. Generative AI covers language models, post-training, prompting, RAG, tools and agents, evaluation, fine-tuning and diffusion. Their syllabi are published and lessons open as they are released.

Do I get a certificate?

Yes. Complete a course's lessons, quizzes and projects to earn a certificate for it, with a link anyone can use to verify it.