The course runs on 17 & 18 July 2025, and will be delivered in person in London. |
Recent advances in AI have the potential to transform both clinical medicine and public health. However, their effective use requires healthcare professionals and stakeholders to understand the key principles of machine learning, computer vision, and large language models underlying these technologies as well as their strengths, limitations, and appropriateness for specific healthcare use cases. There is also a need to understand the current landscape of the regulatory, ethical, and challenges in implementing these technologies in the real world. This course addresses these needs by equipping students to critically appraise and conceptualise 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 Research Group at the London School of Hygiene and Tropical Medicine.
Who is this course for?
The course has been designed for professionals with a health background (doctors, nurses, allied health professionals, epidemiologists, medical statisticians, or any healthcare researchers) with a strong interest in AI in healthcare. No prior knowledge of AI/ML is expected. Applicants should have a good command of English.
This course aims to introduce students to key concepts and applications of AI in health. Specifically, it will equip students with knowledge and skills to critically appraise and plan AI-related health research.
Intended learning outcomes
Upon successful completion of the course, students will be able to:
- Appreciate the range of applications and potential of AI in health
- Understand the key concepts underlying AI in health solutions, including machine learning, deep learning, computer vision, and large language models and gain hands-on experience in coding some example use-cases (NB this will not entail learning to independently code all types of AI models which is beyond the scope of this introductory course).
- Understand how to evaluate AI technologies for health.
- Appreciate key implementation, regulatory, and ethical issues surrounding the use of AI in health.
- Critically appraise AI-related health research.
Session content
Sessions will be split into the following themes:
- Overview of AI/ML in healthcare (lecture)
- Traditional ML methods with a focus on supervised (regression/classification) and unsupervised (clustering, and dimensionality reduction) learning algorithms (lecture and computer practical)
- Modern ML methods with a focus on artificial neural networks, computer vision, and large language models (lecture and computer practical)
- Evaluation of AI/ML in health solutions considering model validation, effectiveness, cost-effectiveness, bias, and monitoring (lecture)
- Ethical, regulatory, and trust issues surrounding the use of AI/ML in health (lecture)
- Critical appraisal of AI/ML-related health research (lecture and practicals applying learning so far to appraise published literature).
Teaching methods/assessments
The course including lectures and practicals (with group discussions) will be delivered in person. Teaching will be conducted synchronously. Participants will also have the opportunity to network with course organisers and other attendees. The course materials, including PowerPoint presentations, extra reading references, and practical code notebooks will be provided electronically.
Computer requirements
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.
Tuition fees for the AI in Health short course in July 2025:
- £600
Applying for this course
Applications for 2025 are now open and can be made via our online application form.
The application deadline is 23 June 2025. 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.
Visas
The student is responsible for obtaining any visa or other permissions to attend the course, and is encouraged to start the application process as early as possible as obtaining a visa for the UK can sometimes take a long time. The Short Courses team can provide supporting documentation if requested.
Accommodation
A list of hotels located in the vicinity of LSHTM, along with further resources for short-term accommodation, can be found on our accommodation pages.