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Applied Artificial Intelligence for Health Research

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The goal of this course is to equip you with sufficient foundational knowledge, but primarily practical coding and engineering skills to ensure that you feel confident applying deep learning to real world health care problems and adapting to the fast paced field as it moves forward in future.

This is an intermediate level course, requiring you to have a working knowledge of Python, including classes and the ability to work with packages such as numpy. It will help you to have studied mathematics at high school, since this course uses concepts such as first order partial derivatives and matrix algebra in its teaching.

This course teaches how to work with image data, which has a richer structure than many other types of data. Thus it is important for you to take the time to understand theses structures, and how they are transformed prior to being used in deep learning models.

Keywords: AI, deep learning, machine learning, python

Target audience: Researcher, Postgraduate student, Clinician, Bioinformatician, Public sector, Research Software Engineer

Resource type: Online Resource

Authors: Cardoso, Jorge; Robinson, Emma; Da Silva, Mariana; Borges, Pedro; Langham, John; Crawford, Andre;

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