Deep Learning Methods for Healthcare

This course is part of Deep Learning for Healthcare Specialization

Instructor: Jimeng Sun

Skills you'll gain

  •   Tensorflow
  •   Jupyter
  •   Keras (Neural Network Library)
  •   Applied Machine Learning
  •   Health Informatics
  •   Deep Learning
  •   Feature Engineering
  •   Image Analysis
  •   Machine Learning
  •   PyTorch (Machine Learning Library)
  •   Computer Vision
  •   Medical Imaging
  •   Python Programming
  •   Dimensionality Reduction
  •   Artificial Neural Networks
  • There are 4 modules in this course

    The first phase of the course will include video lectures on different DL and health applications topics, self-guided labs and multiple homework assignments. In this phase, you will build up your knowledge and experience in developing practical deep learning models on healthcare data. The second phase of the course will be a large project that can lead to a technical report and functioning demo of the deep learning models for addressing some specific healthcare problems. We expect the best projects can potentially lead to scientific publications.

    Week 2 - Convolutional Neural Networks (CNN)

    Week 3 - Recurrent Neural Networks (RNN)

    Week 4 - Autoencoders

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