Csepregi Máté contributed to the kizsi2024/12I-SZ repository by developing and integrating binary assets to enhance onboarding and lay the foundation for future machine learning features. Over two months, he delivered a hands-on Scratch tutorial resource and a machine learning asset, both added as .sb3 files without direct code changes. His work focused on asset management, repository organization, and supporting user self-service learning, using skills in asset packaging and version control with Git. While the scope was limited to asset integration rather than code development, his contributions improved project structure and prepared the repository for upcoming ML experimentation and onboarding.