Target Audience:

This talk targets early- to mid-career software developers (while still appealing to senior and above), computer science students, and anyone who writes code but feels unsure about their math skills. It’s especially valuable for those who want to better understand the numerical foundations of programming (i.e. floating-point behavior, randomness, and performance optimization) and how intuitive number sense can help them debug, design, and think more clearly about code. Additionally it's a great fit for educators or mentors looking to explain complex concepts in a practical, accessible way.

Abstract:

Many developers claim they’re "bad at math," yet mathematical thinking is embedded in everything they do. From loops mirroring sigma notation to optimizing search algorithms through factorization, number sense - the intuitive grasp of patterns, estimation, and numerical relationships - shapes how we perform our jobs. From how we approach a challenge, think through an issue, or write efficient code.

Math in programming goes even deeper than that. Can computers generate true randomness, or is it all just clever illusion? Why does 0.1 + 0.2 ≠ 0.3, and how did floating-point errors lead to multimillion-dollar failures? In this talk, we’ll explore how embracing number sense helps developers troubleshoot bugs, write more scalable code, and unlock a deeper understanding of computation. Math isn’t just for theory, it’s a secret weapon every programmer can wield.