Data and AI Fundamentals

Learning Path: Data Scientist (AI-Focused)

AI-focused Data Scientists extract insights from data and build predictive models to solve business problems. They combine statistics, ML, and domain expertise to turn raw data into decisions that drive organisations forward.

Learning Path: MLOps / AI Infrastructure Engineer

MLOps Engineers bridge the gap between data scientists who build models and the production systems where those models run. They design and maintain the infrastructure, pipelines, and processes that allow models to be trained, evaluated, versioned, deployed, monitored, and retrained reliably.

Learning Path: Data Engineer (AI Pipelines)

Data Engineers build and maintain the infrastructure that collects, stores, transforms, and serves data to AI and ML systems. The AI Pipelines specialisation means focusing on reliable, scalable pipelines that feed training data to models and serve inference-time data to production AI applications. Without good data engineering, ML models cannot be trained or serve real users.