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.
Advanced Deep Learning Methods for Healthcare
Advanced Deep Learning Methods for Healthcare
This course is part of Deep Learning for Healthcare Specialization
Instructor: Jimeng Sun
3,864 already enrolled
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Gain insight into a topic and learn the fundamentals.
Advanced level
Recommended experience
16 hours to complete
3 weeks at 5 hours a week
Flexible schedule
Learn at your own pace
Prepare for a degree
Skills you'll gain
Details to know
Shareable certificate
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Assessments
4 assignments
Taught in English
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This course is part of the Deep Learning for Healthcare Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 4 modules in this course
Attention Models are useful to detect specific features in a data source. We'll explain how it can be applied to the risk of heart failure.
What's included
4 videos3 readings1 assignment1 programming assignment1 discussion prompt
In this week we'll explain the fundamentals of Graph Neural Networks.
What's included
5 videos2 readings1 assignment1 programming assignment
We'll explain the principles behind Memory Networks and how they can be used for predictions in medical applications.
What's included
8 videos2 readings1 assignment
We'll discuss Generative Networks, as well as the method of Variational Autoencoder
What's included
4 videos2 readings1 assignment
Instructor
Offered by
Recommended if you're interested in Machine Learning
Duke University
Johns Hopkins University
Politecnico di Milano
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Taking this course by University of Illinois Urbana-Champaign may provide you with a preview of the topics, materials and instructors in a related degree program which can help you decide if the topic or university is right for you.
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