Health Data Science Foundation
Develop expertise in machine learning and deep learning algorithms for healthcare applications, including medical data analysis and predictive modeling.
Develop expertise in machine learning and deep learning algorithms for healthcare applications, including medical data analysis and predictive modeling.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Deep Learning for Healthcare Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
4.6
(9 ratings)
4,069 already enrolled
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What you'll learn
Process and analyze different types of healthcare data
Implement machine learning models for medical applications
Understand healthcare data standards and their applications
Develop deep neural networks for healthcare problems
Apply predictive modeling in medical scenarios
Skills you'll gain
This course includes:
3.7 Hours PreRecorded video
4 quizzes, 4 programming assignments
Access on Mobile, Tablet, Desktop
FullTime access
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There are 4 modules in this course
This comprehensive course bridges machine learning and healthcare, focusing on the foundational aspects of health data science. Students learn about various types of healthcare data, including electronic health records, medical imaging, and clinical notes, along with relevant data standards. The curriculum covers essential machine learning concepts, from feature construction to deep neural networks, with practical applications in healthcare scenarios. Through hands-on programming assignments and real-world examples, participants develop skills in processing and analyzing healthcare data using modern machine learning techniques.
Introduction
Module 1 · 5 Hours to complete
Health Data
Module 2 · 6 Hours to complete
Machine Learning Basics
Module 3 · 6 Hours to complete
Deep Neural Networks (DNN)
Module 4 · 5 Hours to complete
Fee Structure
Instructor
Professor of Computer Science
Jimeng Sun is a Professor in the Computer Science Department at the University of Illinois Urbana-Champaign (UIUC), where he specializes in applying artificial intelligence (AI) to healthcare. Before joining UIUC, he served as an Associate Professor at the Georgia Institute of Technology and was a researcher at IBM's TJ Watson Research Center. His research focuses on several critical areas, including deep learning for drug discovery, clinical trial optimization, computational phenotyping, clinical predictive modeling, treatment recommendations, and health monitoring.Dr. Sun has made significant contributions to the field, publishing over 120 papers and filing more than 20 patents, with five granted. He has been recognized as one of the Top 100 AI Leaders in Drug Discovery and Advanced Healthcare. His accolades include the SDM/IBM Early Career Research Award in 2017 and multiple best paper awards at prestigious conferences. Jimeng holds a B.S. and M.Phil. in Computer Science from the Hong Kong University of Science and Technology and a Ph.D. from Carnegie Mellon University. At UIUC, he teaches courses such as "Advanced Deep Learning Methods for Healthcare" and "Health Data Science Foundation," where he equips students with the skills necessary to leverage AI in improving healthcare outcomes.
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4.6 course rating
9 ratings
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