Technology areas

Software and web development treated as an engineering discipline: readable code, deliberate architecture, and systems that keep working after you stop looking at them.

Applied machine learning with a working understanding of the mathematics — enough to debug a training run, not just to launch one.

Offensive and defensive practice in the same curriculum: you cannot defend a system whose failure modes you have never produced yourself.

The fundamentals that outlast frameworks — how machines actually run code, and why some solutions scale while others quietly do not.

The operational side of software: reproducible infrastructure, automated delivery and systems you can debug while they are on fire.

Working with real data: modelling, analysis, pipelines and the communication step that turns numbers into a decision.