Worked on the bayesflow-org/bayesflow repository to improve the clarity and accuracy of documentation for diffusion models tutorials. Focused on refining the explanation of the score function and its application in solving reverse stochastic differential equations, the contribution involved correcting a typo and enhancing the tutorial’s instructional content. This targeted documentation update, implemented in Python, aimed to reduce user confusion and streamline onboarding for data science and machine learning practitioners. The work demonstrated careful attention to detail, precise commit practices, and a strong understanding of diffusion processes, resulting in a low-risk, traceable change that aligns with the project’s quality standards.