MSc Data Science

Overview

Data science sits at the intersection of statistics, computing, and domain expertise. This programme teaches you to frame business questions as analytical problems, wrangle messy real-world datasets, and communicate findings to non-technical audiences. Modules cover Bayesian inference, deep learning, NLP, and MLOps. You will work with public datasets from healthcare, finance, and climate science, building a portfolio that demonstrates end-to-end analytical capability.

Every module uses real datasets — never toy CSVs alone. You will document reproducible notebooks and present to a mock executive panel in the capstone. AFU partners with public-health NGOs for anonymised analytics projects.

Who This Programme Is For

• ✦Analysts upgrading from Excel to Python and ML workflows
• ✦Engineers moving into ML engineering or analytics engineering
• ✦Researchers needing formal statistical and computing credentials

Programme Structure & Delivery

Learning Outcomes

• ✦Apply statistical inference and experimental design to business problems
• ✦Build and validate predictive models using scikit-learn, PyTorch, and R
• ✦Design dashboards and narratives that drive executive action
• ✦Implement reproducible data pipelines with version control and testing
• ✦Evaluate AI systems for fairness, bias, and regulatory compliance
• ✦Design A/B tests and interpret results for product and policy teams
• ✦Document model cards and monitoring plans for production ML

Career Pathways

• ✦Data Scientist
• ✦Analytics Engineer
• ✦Business Intelligence Lead
• ✦Quantitative Research Analyst
• ✦AI Product Manager

Curriculum