University of Manchester - AI for Healthcare: Equipping the Workforce for Digital Transformation
- Offered byFutureLearn
AI for Healthcare: Equipping the Workforce for Digital Transformation at FutureLearn Overview
AI for Healthcare: Equipping the Workforce for Digital Transformation
at FutureLearn
Duration | 5 weeks |
Total fee | ₹2,763 |
Mode of learning | Online |
Official Website | Go to Website  |
Credential | Certificate |
AI for Healthcare: Equipping the Workforce for Digital Transformation at FutureLearn Highlights
AI for Healthcare: Equipping the Workforce for Digital Transformation
at FutureLearn
- Duration 5 weeks
- Weekly study 2 hours
- 100% online Learn at your own pace
AI for Healthcare: Equipping the Workforce for Digital Transformation at FutureLearn Course details
AI for Healthcare: Equipping the Workforce for Digital Transformation
at FutureLearn
More about this course
- AI is transforming healthcare in a variety of beneficial ways, from streamlining workflow processes to making more precise patient diagnoses. However, this is not without its challenges.
- The University of Manchester has partnered with Health Education England to create a course for you to see real-world examples of how AI is transforming areas such as radiology, pathology, and nursing.
- On this course, you will develop your own digital skills and increase your understanding of technology for healthcare, so that you can join the conversation on embedding AI in healthcare practice.
AI for Healthcare: Equipping the Workforce for Digital Transformation at FutureLearn Curriculum
AI for Healthcare: Equipping the Workforce for Digital Transformation
at FutureLearn
Motivating AI in healthcare
Getting Started
Joining the Conversation
The Fourth Industrial Revolution
What is artificial intelligence?
AI and machine learning
Machine learning workflow
Data in the machine learning workflow
Data in healthcare
Challenges
How data is being used
Towards the future
Making it work
Ethics and consent
Working in interdisciplinary teams
New ways of working
Supporting and skilling the workforce
Using machine learning for cancer diagnosis
Translation into practice
Looking ahead
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