Mathematics
Machine Learning and Statistics for Health (L6)
Module code: G5221
Level 6
15 credits in spring semester
Teaching method: Lecture, Practical
Assessment modes: Coursework, Unseen examination
This module is designed to provide you with a comprehensive understanding of analytical and interpretative statistical methods and tools essential for solving complex problems in the fields of health and medicine. The module is structured around three overarching areas:
- survival analysis
- classification
- clustering,
This will help you develop a diverse skill set to navigate the intricacies of medical data analysis effectively. Teaching will blend theory and hands-on methods, and reinforce practical skills.
Including supervised and unsupervised learning techniques, such as logistic regression and medical data clustering, this module equips you with the expertise needed to excel in the intricate world of health and medical data analytics. On completion, you’ll confidently tackle real-world healthcare problems using data-driven insights.
Module learning outcomes
- Systematic understanding of and proficiency in the theory and methods of medical statistics and machine learning techniques
- Apply advanced techniques such as non-linear models and clustering to analyse real-world health and medical data
- Apply and interpret results of survival analysis, and statistical learning techniques applied to medical problems
- Use statistical software to enhance a practical understanding of theory application in real-world contexts.