From mid 2018 until early 2020, I ran courses entitled 'Machine Learning for Healthcare' in London. Most resources for learning machine learning were aimed at people from maths or computer science backgrounds, so the course was designed to 'bridge the gap' - by providing a less-technical and more healthcare-tailored introduction.

I no longer have time to run the courses, but have condensed the key points into a series of 9 videos which can watch here. (If you don't have the time / aren't interested enough to watch the full series, consider the one-hour video below which is a condensed version of the main points.)


Check out these blog posts on a range of topics, including signposting to resources, suggestions for incorporating ML into a medical career, key research paper summaries and commonly-asked questions.

If there are any posts you'd like to see made, drop an email to


This is a guest appearance on the 'Big Picture Medicine' podcast, where we talk about about key definitions (AI vs machine learning vs deep learning), the current state of AI in healthcare research, whether AI will replace doctors, how to read medical ML papers and how to get involved:


Here is a one-hour webinar giving an overview of machine learning and it's application in medicine:


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