This intermediate course is designed to help you move from understanding AI concepts to applying deep learning techniques in real health research contexts.
With a strong focus on practical coding and engineering skills, you will learn how to implement simple neural networks from scratch in Python and work with common deep learning models using PyTorch.
The course explores a wide range of healthcare applications, with particular attention to medical imaging data and the challenges of using complex, real-world datasets. By the end, you will be better equipped to understand the strengths and limitations of deep learning, validate models effectively, troubleshoot architectures and adapt modern AI approaches to your own research.
