Gary Sutton is a software engineer and educator focused on the math foundations underneath modern software work — particularly the statistics and probability that show up in production engineering for testing, observability, machine learning, and decision-making under uncertainty.
His CourseFlix listing carries Statistics Every Programmer Needs — a structured treatment of the statistical patterns most working programmers benefit from understanding: hypothesis testing, confidence intervals, distributions, sampling, and the patterns for reasoning about A/B tests and observed metrics.
Material is paid and aimed at developers ready to fill the statistical-foundations gap that most CS curricula underserve. For broader content, see CourseFlix's Python category page where this course sits alongside data-analysis material.
