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AI for Healthcare: Equipping the Workforce for Digital Transformation

University of Manchester via FutureLearn


Expand your digital skills and become a champion for ethical AI

Artificial intelligence is transforming healthcare systems around the world. From streamlining workflows to making more precise diagnoses, the benefits of AI for healthcare are numerous. But with those benefits come logistical, ethical, and financial challenges.

The University of Manchester has partnered with Health Education England to bring you this course exploring the issues and opportunities of AI in healthcare.

Over the five weeks of the course, you’ll look at a range of real-world examples of how AI is used in radiology, pathology, nursing, and other areas.

Understand the possibilities of AI for healthcare

The course will start by introducing the context of AI in healthcare.

You’ll learn what AI is, how it could benefit the healthcare sector, and who’s driving efforts to harness AI for public health.

Explore logistical and ethical challenges around data use and AI

After examining the potential uses of AI in healthcare, you’ll explore the challenges that come with them.

In Weeks 3 and 4, you’ll look at some potential problems and solutions relating to the use of data and AI in various areas of the healthcare sector.

Upskill and help build a digitally literate workforce

As well as an understanding of current AI technology, you’ll gain the digital skills you need to incorporate it into your own practice.

By the end of the course, you’ll be a digitally literate member of the healthcare workforce, ready to contribute to the future of health AI.

This course is designed for health and social care professionals in the UK. It will also be relevant to non-UK healthcare professionals who want to learn more about general issues, challenges, and opportunities surrounding the use of AI in all healthcare systems.

Finally, the course provides useful knowledge for anyone interested in emerging professional uses of AI. This may include clinical data scientists, medical software engineers, digital medicine specialists.


  • 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

Taught by

Andy Brass


4.4 rating at FutureLearn based on 35 ratings

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