Overview

Master AI & Machine Learning for 50% Off

Go under the hood of AI — neural networks, real-world applications & more. Designed by UNSW experts.

Gain practical AI literacy skills tailored specifically for medical education through this course designed to prepare future clinicians for AI-integrated healthcare environments. Apply the TRACE verification framework to evaluate AI-powered study tools, identify hallucinations in medical content, and maintain academic integrity throughout your studies. Develop critical evaluation skills for AI-generated clinical outputs encountered during ward placements, while preserving independent clinical reasoning and upholding patient privacy obligations in AI-enabled hospital settings. Implement structured exam preparation strategies using the 50/30/20 balanced model, recognising the risks of over-reliance on AI tools when preparing for OSCEs and clinical examinations. Analyse AI-powered research tools for reliability, apply reference verification protocols to detect fabricated citations, and adhere to institutional and journal AI disclosure standards in academic writing. Design a personal AI literacy development plan that addresses specialty-specific AI disruption, builds a competitive AI-literate professional profile, and incorporates awareness of the medico-legal landscape facing junior doctors entering an increasingly AI-driven healthcare system.

Syllabus

Apply practical AI literacy skills across study, clinical placements, examinations, research, and career planning while maintaining academic integrity, patient safety, and independent clinical reasoning.
Apply AI-powered study tools using the TRACE verification framework to enhance learning while maintaining academic integrity and identifying AI hallucinations in medical content.
Evaluate AI-generated clinical outputs encountered during ward placements, maintain independent clinical reasoning, and uphold patient privacy obligations in AI-enabled hospital environments.
Implement structured AI-assisted exam preparation strategies using the 50/30/20 balanced model while recognising the risks of AI-dependency on OSCE and clinical examination performance.
Analyse AI-powered research tools for reliability, apply reference verification protocols to detect fabricated citations, and adhere to institutional and journal AI disclosure standards in academic writing.
Analyse AI-powered research tools for reliability, apply reference verification protocols to detect fabricated citations, and adhere to institutional and journal AI disclosure standards in academic writing.
Design a personal AI literacy development plan that addresses specialty-specific AI disruption, builds an AI-literate professional profile, and incorporates awareness of the medico-legal landscape for junior doctor.