Understanding and Development
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Master of Research & Learning
(M.RL) - Data Science
Specialisations
Government • National Statistics • Multilateral
Private Sector • Finance • Consulting
NGOs • Development • Food Security
Project Data Management Systems
Develops the ability to design, implement, and lead data management systems within project and programme environments
Course Focus
★ Programme-level data strategy, adaptive management, portfolio oversight, and leading data teams.
Research Strand
Leading applied research within programme environments — commissioning and synthesising evidence
Specialisation Context
A - Policy
Advanced PIS architecture for government and multilateral programmes: predictive planning, national data systems, and cross-ministry coordination
B - Business
Enterprise PIS leadership: portfolio-level information systems, predictive performance analytics, and corporate governance integration
C - Livelihoods
Advanced PIS architecture for development programmes: predictive vulnerability tracking, multi-donor data environments, and impact forecasting.
Technical Learning Topics - by Specialisation
- National programme-level M&E architecture and standards
- Adaptive management in government programme delivery
- Portfolio performance monitoring for public sector programmes
- Outcome harvesting for government and multilateral contexts
- Systematic reviews for government evidence synthesis
- Predictive decision-making for public resource allocation
- Risk-adjusted performance modelling for national budgets
- Multi-ministry coordination and reporting systems
- Evidence commissioning for policy decision-making
- Digital transformation of national M&E infrastructure
Assessment Tasks
Develop a portfolio-level research and learning strategy with an evidence synthesis plan
Software & Tools
Primavera P6, MS Project Online, Tableau (portfolio), Python, NVivo, Power BI, Jira Advanced
AI Applications
AI portfolio management tools; predictive resource allocation; ML-based risk identification.