Course Description
Meta-analysis has long been the gold standard for synthesizing research evidence. In today’s data-intensive world, however, traditional meta-analytic approaches must evolve to accommodate high-dimensional datasets, machine learning outputs, real-time data streams, and AI-assisted research workflows.
This course bridges classical statistical meta-analysis with modern data science and artificial intelligence techniques. Participants will learn how to conduct rigorous evidence synthesis while leveraging scalable computation, automated extraction pipelines, and AI-assisted modelling.
Designed for data professionals, researchers, public health analysts, and policy-driven organizations, this program equips participants to lead evidence-based decision-making in complex, data-rich environments.