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
Organisational Data Analytics
Develops the ability to analyse, visualise, and communicate data to drive decisions
Course Focus
★ PREDICTIVE ANALYTICS MASTERY — ML model interpretation, AI analytics, and enterprise leadership.
Research Strand
Leading applied analytics research; producing original intelligence that advances the field.
Specialisation Context
A - Policy
Predictive policy modelling: disease surveillance, economic forecasting, electoral trend analysis.
B - Business
Predictive business analytics: demand forecasting, churn prediction, risk modelling.
C - Livelihoods
Predicting vulnerability, crop failure risk, and livelihood shock using household panel data.
Technical Learning Topics - by Specialisation
- Supervised ML for public health and policy classification
- Logistic regression for policy outcome prediction
- Decision trees and Random Forest for social indicator modelling
- Time-series forecasting for economic and demographic trends
- Model validation for policy research credibility
- Model explainability (SHAP) for government accountability
- NLP for policy document and public opinion analysis
- AI-assisted policy analytics and evidence synthesis
- Predictive research design for government evaluations
- Ethical AI and algorithmic bias in public policy
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.