UIUC - Deep Learning Methods for Healthcare
- Offered byCoursera
Deep Learning Methods for Healthcare at Coursera Overview
Duration | 22 hours |
Total fee | Free |
Mode of learning | Online |
Official Website | Explore Free Course  |
Credential | Certificate |
Deep Learning Methods for Healthcare at Coursera Highlights
- Earn a Certificate upon completion from University of Illinois at Urbana-Champaign
Deep Learning Methods for Healthcare at Coursera Course details
- This course covers deep learning (DL) methods, healthcare data and applications using DL methods
- 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
Deep Learning Methods for Healthcare at Coursera Curriculum
Week 1 - Embedding
Welcome to this course!
General Embedding: Word2Vec
General Embedding: t-SNE
EHR Embedding: Med2Vec
EHR Embedding: MiME
About this course
Slides: Embedding
Textbook Chapter 5 (Embedding)
Embedding
Week 2 - Convolutional Neural Networks (CNN)
Introduction: Convolution and Pooling
Convolution
Pooling
CNN Architectures
Healthcare Applications of CNN
Slides: CNN
Textbook Chapter 6 (Convolutional Neural Networks (CNN))
CNN
Week 3 - Recurrent Neural Networks (RNN)
Basic RNN Concepts & Structure
Back Propagation Through Time (BPTT)
Long Short Term Memory Networks (LSTM)
Gated Recurrent Unit (GRU)
Healthcare Applications
Slides: RNN
Textbook Chapter 7 (Recurrent Neural Networks (RNN))
RNN
Week 4 - Autoencoders
Autoencoders: Intro
Autoencoders: Properties
Autoencoders: Variants
Autoencoders: Application
Slides: Autoencoders
Textbook Chapter 8 (Autoencoders (AE))
Autoencoders
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