Learning Outcomes. Subject-specific: Knowledge, Understanding and Skills

At the end of the course the students should be able to demonstrate subject-specific knowledge, understanding and skills and have the ability to:

• Develop an understanding of the underlying principles of artificial intelligence.
• Identify and describe different intelligent agents and their operating environments
• Understand different problem-solving and planning strategies, with a particular focus on constraint satisfaction problems and multi-agent planning.
• Justify and critique the use of different learning methods for medical and healthcare applications, in particular those used in temporal reasoning tasks.
• 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.

Learning Outcomes. General: Knowledge, Understanding and Skills

On successful completion of this module the student should be able to:

• Study autonomously and undertake activities/projects with minimum guidance.
• Effectively communicate and critically assess own work in discussion groups, online forums and presentations.
• Read, understand and critique an AI-healthcare application in the research literature.
• Successfully work in a team during computer group lab sessions.
• Show confidence in the use of Python to implement AI techniques.

Requirements:

• Introduction to Health Informatics (7PAVITHI)
• This workshop will assume that participants have a basic knowledge of the high-level programming language, python. Participants will need their own laptop/computer with python installed.