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The Data Science pathway of this science-led programme combines knowledge of risk and disaster reduction with statistical and computational skills and digital health in emergencies.
Please note this pathway is not currently running. See the Risk and Disaster Science MSc page intead.
- Why is Data Science important in disaster risk reduction?
Data science provides tools to measure and understand risks, vulnerabilities and resilience. It is fundamental for decision-making in disaster response and recovery. It helps us to understand how disaster risk may evolve in the future and how science and technology may be able to improve preparedness.
- What is the Data Science Pathway?
This pathway begins at an introductory level and continues with a range of optional modules covering more specialized knowledge in statistical computing and modelling. Students will be able to analyse both qualitative and quantitative data and communicate the results to wide and varied audiences that have different objectives with regard to the issues and potential solutions.
As a leading Global university, we aim to nurture future leaders who are equipped with scientific knowledge of disasters and professional skills in industry standard software.- How to apply
Applicants who wish to choose this optional pathway must apply through the Risk and Disaster Science MSc Programme.
After pre-enrolling on the Risk and Disaster Science MSc, students will be eligible to choose the Data Science Pathway and have the opportunity to enroll in up to two optional modules from UCL Department of Statistical Science.
Teaching and Learning
Learn from world-class researchers and professionals delivering the programme through a combination of lectures, class discussions, problem-solving exercises, practicals, field trips, directed reading, student-led dialogue, and a practitioner-led real-time disaster scenario event. Assessment is by individual and group presentations, coursework, written examinations, and a research project.
Programme Specific Themes
Data Science
- Statistical computing and modelling of natural and anthropogenic hazards, humanitarian and health crises, conflict, and climate change.
Science of Earth and Space Hazards
- Analyze different hazard risks: seismicity, space weather, epidemics, conflict and climate
- Scenarios and case studies drawn globally to provide breadth of experience
IRDR MSc themes
Understanding Vulnerability
- From fragility curves describing damage to buildings to social vulnerability of individuals and society
Quantifying Risk
- What is risk and how do we measure it?
- Components of risk: exposure, hazard, vulnerability
Multidisciplinary Holistic Approaches
- Integrating scientific knowledge into disaster risk reduction research, policy and practice
- Communicating with stakeholders
Managing Disasters
- How to apply plans to manage real emergencies
