Big Data Analytics for Healthcare

Big Data Analytics for Healthcare

Course
en
English
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Source
  • From www.coursera.org
Conditions
  • Self-paced
  • Free Access
  • Free certificate
More info
  • Introductive Level

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Course details

Syllabus

Large amounts of heterogeneous medical data have become available in various healthcare organizations (payers, providers, pharmaceuticals). Those data could be an enabling resource for deriving insights for improving care delivery and reducing waste. The enormity and complexity of these datasets present great challenges in analyses and subsequent applications to a practical clinical environment. In this course, we introduce the characteristics and related analytic challenges on dealing with clinical data from electronic health records. Many of those insights come from medical informatics community and data mining/machine learning community. There are three thrusts in this course: Application, Algorithm and System

Prerequisite

None.

Instructors

  • Jimeng Sun - School of Computational Science and Engineering | College of Computing

Editor

The Georgia Institute of Technology, also known as Georgia Tech or GT, is a co-educational public research university located in Atlanta, Georgia, USA. It is part of the wider University System of Georgia network. Georgia Tech has offices in Savannah (Georgia, USA), Metz (France), Athlone (Ireland), Shanghai (China), and Singapore.

Georgia Tech's reputation is built on its engineering and computer science programmes, which are among the best in the world5,6. The range of courses on offer is complemented by programmes in the sciences, architecture, humanities and management.

Platform

Coursera is a digital company offering massive open online course founded by computer teachers Andrew Ng and Daphne Koller Stanford University, located in Mountain View, California. 

Coursera works with top universities and organizations to make some of their courses available online, and offers courses in many subjects, including: physics, engineering, humanities, medicine, biology, social sciences, mathematics, business, computer science, digital marketing, data science, and other subjects.

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