Deep Learning for Healthcare

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

Instructor: Jimeng Sun

Advanced Level • 2 months to complete at 10 hours a week • Flexible Schedule

Skills You'll Gain

Graph Theory
Image Analysis
Machine Learning
Machine Learning Methods
Network Analysis
Computer Vision
Tensorflow
Applied Machine Learning
Keras (Neural Network Library)
Unsupervised Learning
Generative AI
PyTorch (Machine Learning Library)

Shareable Certificate

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Outcomes

  • Learn in-demand skills from university and industry experts
  • Master a subject or tool with hands-on projects
  • Develop a deep understanding of key concepts
  • Earn a career certificate from University of Illinois Urbana-Champaign

3 courses series

This course is intended for persons involved in machine learning who are interested in medical applications, or vice versa, medical professionals who are interested in the methods modern computer science has to offer to their field. We will cover health data analysis, different types of neural networks, as well as training and application of neural networks applied on real-world medical scenarios.We cover deep learning (DL) methods, healthcare data and applications using DL methods. The courses include activities such as video lectures, self guided programming labs, homework assignments (both written and programming), and a large project. 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.

This course covers deep learning (DL) methods, healthcare data and applications using DL methods. The courses include activities such as video lectures, self guided programming labs, homework assignments (both written and programming), and a large project.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.

This course covers deep learning (DL) methods, healthcare data and applications using DL methods. The courses include activities such as video lectures, self guided programming labs, homework assignments (both written and programming), and a large project.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.

Learner Testimonials

Felipe M.
Felipe M. • Learner since 2018

To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood.

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Jennifer J. • Learner since 2020

I directly applied the concepts and skills I learned from my courses to an exciting new project at work.

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Larry W. • Learner since 2021

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