| The course runs from 24 to 27 November 2026, and will be delivered online. |
Recent developments in Artificial Intelligence (AI) have the capacity to significantly reshape clinical practice and public health. To apply these technologies effectively, healthcare professionals and other stakeholders must understand the fundamental concepts behind machine learning, computer vision, and large language models, along with their capabilities, constraints, and suitability for particular healthcare applications.
This online course introduces the key concepts and applications of AI in health, while exploring the ethical, regulatory and implementation challenges involved in using AI technologies in real-world settings. Participants will develop the knowledge and skills to critically appraise AI-related health research and conceptualise responsible AI applications in health, fostering informed decision-making in a rapidly evolving field. The course is organised and taught by members of the AI in Global Health and Healthcare Research Group at the London School of Hygiene & Tropical Medicine.
Who is this course for?
The course has been designed for professionals with a health, clinical, research or public health background who want to understand how artificial intelligence and machine learning are being used in healthcare.
It is suitable for:
- doctors, nurses and allied health professionals
- epidemiologists and public health professionals
- medical statisticians and data-focused health researchers
- healthcare researchers and policy professionals
- professionals interested in AI applications in clinical medicine, public health or global health
No prior knowledge of artificial intelligence or machine learning is required. Applicants should have a good command of English.
This course introduces the key concepts, methods and applications of artificial intelligence in health. By the end of the course, participants will be able to critically appraise AI-related health research and begin planning responsible AI research or implementation projects in healthcare, public health or global health settings.
Intended learning outcomes
Upon successful completion of the course, participants will be able to:
- Appreciate the range of current and emerging applications of AI in healthcare, public health and global health.
- Understand the fundamental concepts behind AI in healthcare, including machine learning, deep learning and large language models.
- Evaluate AI technologies for health, including issues related to validation, effectiveness, cost-effectiveness, bias and monitoring.
- Discuss regulatory, implementation and ethical issues surrounding the use of AI and machine learning in health.
- Critically appraise published research on AI, machine learning and health.
Teaching methods and course structure
Over the 4 days, participants can expect a varied mix of lectures, computer-based practicals, case studies, group discussions and critical appraisal activities. The course is delivered fully online through a combination of synchronous live teaching and asynchronous learning, which may include pre-recorded lectures, set readings and tasks.
Participants will also have the opportunity to network with course organisers and other attendees. Course materials, including PowerPoint presentations, additional reading references and practical code notebooks, will be provided electronically.
The course is not assessed.
Course structure (indicative)
Day 1
- An overview of AI in health
- Introduction to machine learning for health (lecture and practical)
Day 2
- Introduction to deep learning for health (lecture and practical)
- Analysis of medical images (lecture and practical)
Day 3
- Introduction to foundation models for health (lecture and practical)
- Alignment of large language models (practical)
Day 4
- Evaluation of AI-based healthcare solutions (lecture)
- Implementation of AI-based healthcare solutions (lecture)
- Should I implement this AI in health solution? (Practical)
Learning time of approximately 3 hours per day.
Live learning content will take place between 11am and 2pm GMT.
Requirements and selection criteria
To participate in this course you’ll need a laptop with internet access and a Gmail account. All coding will be done on Google Colab, so no special software or hardware is required. English language IELTS 7 or above (of equivalent) required.
Applicants will need to submit a motivational statement (max 500 words) demonstrating their healthcare background, a strong interest in applications of AI in healthcare, and a clear understanding of how this course aligns with their professional development goals.
Tuition fees for the AI in Health online short course in November 2026:
- £630
Applying for this course
Applications for 2026 are now open and can be made via our online application form.
The application deadline for this course is 27 October 2026, 23:59 UK time. We strongly advise that you apply early as courses may close earlier than the stated deadline if they become full.
Please read LSHTM's Admissions policies prior to submitting your application.