Learning resources

Our approach

Education and teaching plays a central role in life at DeepMind.

We’re always learning ourselves, and we partner with world-leading universities and organisations to broaden participation in science and invest in the future of research and education.

Increasing access

We produce teaching materials and learning resources for people of all abilities.

Many of our researchers also hold teaching posts at universities including Cambridge, Oxford, Imperial College, MIT, Alberta, McGill and elsewhere.

Below, you’ll find some of the resources we’ve created to help people at different stages of their learning journey to find out more about AI.

University-level resources

From presentations and lecture slides to reading material and complete courses, our team has created a range of teaching resources to inspire and support students interested in learning about AI research. Many of our resources are created in collaboration with universities, such as the UCL Centre for Artificial Intelligence.

Portraits of Researcher Scientists Hado van Hasselt and Diana Borsa

Reinforcement Learning Lecture Series 2021

Thirteen-part series, created in collaboration with UCL, covering everything from dynamic programming to deep reinforcement learning.

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Portraits of Research Scientists Thore Graepel and Irina Higgins

Deep Learning Lecture Series 2020

Twelve lectures, in collaboration with UCL, ranging from the fundamentals of neural networks to advanced ideas like memory, attention, and GANs.

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Portrait of University of Alberta's Martha White and Adam White

Coursera: Reinforcement Learning

Four-course specialisation for undergrads taught by the University of Alberta's Martha White with her colleague and DeepMinder Adam White.

Explore on Coursera

Portrait of Research Scientist David Silver

Introduction to Reinforcement Learning

Classic 10-part lecture series delivered by DeepMind Principal Research Scientist David Silver, the creator of AlphaZero.

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Portrait of Research Scientist Hado van Hasselt

Reinforcement Learning Lecture Series 2018

Ten part, self-contained introduction to RL and deep RL, done in collaboration with UCL. Complements the Deep Learning Lecture Series.

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Portrait of Research Scientists Raia Hadsell and James Martens

Deep Learning Lecture Series 2018

Eight-part series, done in collaboration with UCL, that explores topics ranging from NLP and optimisation to generative models. Complements the Reinforcement Learning Lecture Series 2018.

Find out more

Community resources

Engaging with communities around the world is important to widen access and participation in AI research.

We’re proud to support groups bringing together and amplifying the voices of people with different experiences, knowledge and backgrounds.

We support our researchers and engineers who helped establish and organise several global education initiatives including the Deep Learning Indaba in Africa, North Africa and Middle East Summer School in Machine Learning (NASSMA), Khipu AI in South America, the Eastern European Machine Learning Summer School (EEML), the Southeast Asia Machine Learning School (SEAMLS), and the AI4Good Summer Lab in Canada.

Along with researchers and volunteers from many other organisations, our researchers and engineers have helped create a wide variety of practical teaching resources used by these organisations:

Deep Learning Indaba: 2019 practicals

Deep Learning Indaba: 2019 lectures

Khipu: 2019 practicals

NASSMA: 2019 practicals

NASSMA: 2019 lectures

EEML: 2020 practicals

EEML: 2020 talks

A commitment to learning

Our approach

Education and teaching plays a central role in life at DeepMind.

We’re always learning ourselves, and we partner with world-leading universities and organisations to broaden participation in science and invest in the future of research and education.

Increasing access

We produce teaching materials and learning resources for people of all abilities.

University-level resources

Community resources

Engaging with communities around the world is important to widen access and participation in AI research.

We’re proud to support groups bringing together and amplifying the voices of people with different experiences, knowledge and backgrounds.