Deep Learning for Healthcare Specialization

Neural Networks in Applied Medicine. Learn the latest cutting-edge methods in Deep Learning for Medical Applications

Instructor: Jimeng Sun

Skills you'll gain

  •   Graph Theory
  •   Generative AI
  •   Image Analysis
  •   Network Analysis
  •   Applied Machine Learning
  •   Unsupervised Learning
  •   Machine Learning
  •   Machine Learning Methods
  •   Deep Learning
  •   Artificial Neural Networks
  •   Supervised Learning
  •   Health Informatics
  • Specialization - 3 course series

    Learners will be able to apply the theoretical concepts in autograded programming assignments that use training data we provide for use with different types of neural networking algorithms. The technology used is (among others) Jupyter Notebooks / PyTorch.

    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.

    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.

    Deep Learning Methods for Healthcare

    Advanced Deep Learning Methods for Healthcare

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