AI in Health Analytics

Discover the principles behind AI and learn how to apply, assess and validate simple techniques for health analytics using Python.

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30 hours

No pre-requisites

Introductory

Course information

This course introduces you to the practical use of artificial intelligence in health-related research and professional settings. Designed for those with little or no programming experience, it will help you understand how AI can be applied to common problems in healthcare, from analysing complex data to supporting smarter decision-making.

Through a flexible learning format, you will build the knowledge and confidence to start implementing standard AI techniques in Python. Whether you work in a clinical, administrative or academic role, this course will give you a solid foundation to explore how AI can support your current work and prepare you for future opportunities in digital health.

Learning objectives

Develop an understanding of the underlying principles of artificial intelligence

Understand different problem-solving and planning strategies, with a particular focus on graph-based searching algorithms, evolutionary and particle swarm algorithms, and constraint satisfaction problems identify and describe different approaches for modelling uncertainty within AI

Justify and critique the use of different learning methods for medical and healthcare applications, in particular those based on neural networks and deep learning paradigms

Be familiar with the principles of reinforcement learning and other goal-oriented algorithms

Be able to develop simple AI techniques, assess their quality and validate them using Python software

Enroll on this course