MSc Health Data Science
Course Overview
This Master's programme prepares graduates from biomedical, clinical, and computational backgrounds for careers at the intersection of AI and healthcare. Students will learn to design and perform advanced analyses to solve practical medical questions using cutting-edge computational methods. The curriculum provides comprehensive training for health data science roles within academia, industry, and national health services.
Key Program Highlights
- Focus on applying AI and machine learning techniques to clinical and biomedical data
- Training in clinical bioinformatics, health informatics, and integrated multimodal data analysis
- Designed for students from both medical/clinical and computer science/mathematics backgrounds
- Prepares graduates for high-demand careers in academia, the healthcare industry, and national health services
- Led by active researchers with expertise in AI applications for cancer risk prediction and clinical bioinformatics
Course Overview
This Master's programme prepares graduates from biomedical, clinical, and computational backgrounds for careers at the intersection of AI and healthcare. Students will learn to design and perform advanced analyses to solve practical medical questions using cutting-edge computational methods. The curriculum provides comprehensive training for health data science roles within academia, industry, and national health services.
Key Program Highlights
- Focus on applying AI and machine learning techniques to clinical and biomedical data
- Training in clinical bioinformatics, health informatics, and integrated multimodal data analysis
- Designed for students from both medical/clinical and computer science/mathematics backgrounds
- Prepares graduates for high-demand careers in academia, the healthcare industry, and national health services
- Led by active researchers with expertise in AI applications for cancer risk prediction and clinical bioinformatics
Requirements
Modules
- Data Analytics and Statistical Machine Learning for Health Data Science
- Essentials of Mathematics, Statistics and Programming
- Foundations of Computing Practices in Health Data Science
- Epidemiology and Health Informatics
- Health Data Fundamentals
- Integrative Multimodal Data Analytics
- Health Data Analytics
- Health Data Science Challenges
- Interdisciplinary Health Data Research Project
