This repository is part of a curated collection of academic and engineering projects and is maintained in a finalized and stable state. The project is preserved as a complete and authoritative record, with its scope and contents intentionally fixed to ensure long-term academic and professional reference.

As a finalized project, only the version listed below is authoritative:

In accordance with established academic and professional standards for security disclosure, security-related observations associated with this project are documented through formal scholarly channels.

To document a security concern, communication is facilitated with the project curators:

• Curator: Amey Thakur
• Collaborator: Mega Satish
• Method: Reports are submitted via the repository’s GitHub Issues interface to formally record security-related findings.

Submissions include:

1. A precise and technically accurate description of the identified issue.
2. Demonstrable steps or technical evidence sufficient to contextualize the finding.
3. An explanation of the issue’s relevance within the defined scope of the project.

This project consists of a curated collection of Python programming scripts, Jupyter Notebooks, and machine learning models, designed for educational and archival purposes in the field of Data Science.

• Scope Limitation: This policy applies exclusively to the documentation, code, and asset resources contained within this repository and does not extend to the runtime environment (Python/PyPI) or third-party dependencies.

This repository is preserved as a fixed academic and engineering project. Security-related submissions are recorded for documentation and contextual reference and do not imply active monitoring, response obligations, or subsequent modification of the repository.

This document defines the security posture of a finalized Python Crash Course project.