Why It Matters
Many technical subjects use probability casually before they need it rigorously. That works until the model depends on what is being integrated, which events are measurable, how probability mass is assigned, or what limit is being taken.
Measure theory gives those questions a shared language. It is useful preparation for statistics, Bayesian inference, reinforcement learning, physics simulation, quantum-mechanical models, and other systems where probability is not just a helper function.
Reading Context
The original post linked a PDF textbook introduction to measure theory as a practical starting point for these areas.