Integrated Care System (ICS) analysts are being offered the opportunity to learn today’s most in-demand machine learning skills from experts.
The course, which would usually cost analysts £1,470 to attend, is the first offering from the Population Health Analytics Centre of Excellence, part of AnalystX, and is available to attend free of charge for suitable candidates
The offer is an online four-day machine learning course led by Amazon Web Services (AWS), providing key skills for ICS teams looking to achieve impactful change in the healthcare system.
The Health Economics Unit (HEU) is delighted to be a part of the Centre of Excellence, providing local analytical teams in ICS with training in machine learning and complex analytical techniques. Other partners include NHS England and Improvement, Public Health England and NHSX.
Course attendees will receive accredited training from AWS, a strategic partner of AnalystX, teaching analysts to use machine learning to tackle real problems in healthcare.
By the end of the course, analysts will have built, trained, evaluated and deployed a machine learning model.
This is the first of a series of courses being offered by the Population Health Analytics Centre of Excellence, to teach ICS Analysts baseline skills in areas including machine learning and complex analytical techniques.
HEU Senior Econometrician Bruno Petrungaro said: “Machine learning unlocks new ways to accelerate progress in meeting our most critical health and care challenges.
“Through this collaboration with AWS, ICS analysts will gain the skills they need to start using machine learning in their local areas, building strong and effective integrated care systems across England.”
The course, which is entirely online, will be run twice; on October 4-7 and October 18-21, and analysts can specify their preferred dates when applying.
See a full breakdown of the course here.
Already have the machine learning skills needed to help the NHS recover from the pandemic? Don’t miss out on your chance to enter the AnalystX machine learning challenge.