Oxford Machine Learning Summer Schools (OxML) are one of our annual events that aim to provide the participants with best-in-class training on a broad range of advanced topics and developments in machine learning (ML) — including, deep learning. While the school covers the key topics in domains such as Bayesian ML, Computer Vision, NLP and reinforcement learning (as well as areas such as Causal ML, Topological ML, and Transfer Learning that the field is showing a growing interest in).


The first OxML summer school (OxML 2020) was organised by AI for Global Goals and in partnership with CIFAR, Uni. of Oxford's Said Business School – Entrepreneurship Centre, and Uni of Oxford's Deep Medicine Program (17-25 Aug, 2020), hosting 350+ AI talents from 70 countries. OxML 2020 had a special focus on medicine (UN's SDG #3), through a range of applied talks at the interface of machine learning and healthcare/biomedical sciences (e.g., medical imaging, genetics, drug discovery, and learning from multi-modal medical data).

This year, OxML 2021 (9-20 August, 2021) is organised by AI for Global Goals, and in collaboration with CIFAR and Uni of Oxford's Deep Medicine Program. This year, in addition to SDG #3 (healthcare/medicine), the school will have additional focus areas such as AI for good (e.g., climate action, emerging risks, ESG, and more). This will enable us to cover a broader range of global goals from a machine learning perspective.

In order to provide the school's diverse participants with the necessary background for the advanced topics in ML/DL, the school will also include a series of lectures on ML fundamentals (during the onboarding week, i.e., Jul 19-21).

In addition to OxML summer schools, AI for Global Goals will host a number of advanced ML courses, winter/summer schools, workshops and hackathons on broader SDG related areas in the coming months.