

University of Illinois Urbana Champaign - Health Data Science Foundation
- Offered byCoursera
- Public/Government Institute
Health Data Science Foundation at Coursera Overview
Duration | 24 hours |
Total fee | Free |
Mode of learning | Online |
Official Website | Explore Free Course |
Credential | Certificate |
Health Data Science Foundation at Coursera Highlights
- Earn a Certificate upon completion from Coursera
- Get flexible deadlines in accordance to student's schedule
- Course 1 of 3 in the Deep Learning for Healthcare Specialization
- Advanced Level We recommend a solid foundation in one of the fields adjacent to the topic of the course, such as Computer Science, Machine Learning, Medicine.
- Approx. 24 hours to complete
- English Subtitles: English
Health Data Science Foundation at Coursera Course details
- 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
- Students 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, students will build up their 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
Health Data Science Foundation at Coursera Curriculum
Week 1 - Introduction
Welcome to this course!
Introduction: Part 1
Introduction: Part 2
About this course
Slides: Introduction
Textbook Chapter 1 (Introduction)
Introduction
Week 2 - Health Data
Health Data - Introduction
Health Data: EHR, Notes
Health Data: Claims, Signals
Health Data: Images, Literature, Drugs
Health Data Standards: Intro & ICD
Health Data Standards: CPT, LOINC, NDC
Health Data Standards: SNOMED
Health Data Standards: UMLS
Slides: Health Data
Slides: Health Data Standards
Textbook Chapter 2 (Health Data)
Health Data
Week 3 - Machine Learning Basics
Prediction Target
Cohort Construction
Feature Construction
Predictive Model and Evaluation
Dimensionality Reduction
Clustering
Performance Metrics
Classification Metrics
Regression and Clustering Metrics
Slides: Supervised Learning
Slides: Unsupervised Learning
Slides: Evaluation
Textbook Chapter 3 (Machine Learning Basics)
Machine Learning Basics
Week 4 - Deep Neural Networks (DNN)
Single Neuron Basics
Training a Single Neuron: SGD
Forward and Backward Computation
Multilayer Neural Network
Slides: Deep Neural Networks
Textbook Chapter 4 (Deep Neural Networks (DNN))
Deep Neural Networks
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