# ai-engineering-hub — Citation & License Notice

> 🌐 Language: [繁體中文](AI_ENGINEERING_HUB_REFERENCE.md) ｜ English ｜ [Deutsch](AI_ENGINEERING_HUB_REFERENCE_DE.md) ｜ [Français](AI_ENGINEERING_HUB_REFERENCE_FR.md) ｜ [Español](AI_ENGINEERING_HUB_REFERENCE_ES.md) ｜ [日本語](AI_ENGINEERING_HUB_REFERENCE_JA.md) ｜ [한국어](AI_ENGINEERING_HUB_REFERENCE_KR.md)

The case list and categories in part of this methodology's [`04_Scenarios/LLM_APPS_CASE_INDEX.md`](../04_Scenarios/LLM_APPS_CASE_INDEX.md) (LLM application case index) are referenced from **patchy631/ai-engineering-hub**. This document records the upstream source, license terms, and scope of citation.

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## 1. Upstream Project

| Field | Value |
| --- | --- |
| **Project** | ai-engineering-hub |
| **Author** | patchy631 (incl. the "Daily Dose of Data Science" newsletter) |
| **GitHub URL** | <https://github.com/patchy631/ai-engineering-hub> |
| **License** | **MIT License** |
| **Content** | 93+ runnable AI engineering projects across beginner / intermediate / advanced levels; includes Jupyter Notebooks and Python source code |

## 2. What It Is

A **code-first AI engineering learning hub** — 93+ production-ready projects across OCR & Vision, chat interfaces, RAG systems, agents & multi-agent, voice & audio, fine-tuning, advanced infrastructure (MCP), and model comparisons. Unlike a plain link directory, it provides runnable code implementations and a structured, progressive learning path.

## 3. What We Cited

| Scope | Treatment |
| --- | --- |
| **Representative project names and categories** | Cited as index entries in `LLM_APPS_CASE_INDEX.md` (source tag H) |
| **L1-L5 mapping, course mapping, application-scenario notes** | This methodology's original work |
| **The projects' source code / Notebooks** | Not reproduced, not forked; learners clone from upstream if they want to build |

> The index covers the named, representative projects of ai-engineering-hub; for the full 93+ list see the upstream repo — more can be added to the index over time.

## 4. License Summary

ai-engineering-hub is under the **MIT License** — permitting free use, modification, redistribution, and commercial use, including as part of a proprietary product. The only condition is preserving the MIT copyright notice and license text when redistributing the source.

This methodology does **not redistribute** its source code — it only cites representative project names and categories as an index in `LLM_APPS_CASE_INDEX.md`. Learners wishing to actually run a project should obtain it from the upstream repo and comply with its MIT terms.

## 5. Citation Format for Learners

> Projects indexed from ai-engineering-hub by patchy631 — <https://github.com/patchy631/ai-engineering-hub> (MIT License)

## 6. Disclaimer

Any mapping of ai-engineering-hub projects onto L1-L5 and courses in this methodology represents the interpretation of the methodology author (Morris Lu / Tiger AI 虎智科技) and does not represent the official position of patchy631. The projects are mostly learning / starter implementations; enterprise adoption must apply this methodology's governance mechanisms (human Gate, Evidence, Stage Gate, security review). If the upstream project list changes in newer versions, refer to the [upstream repository](https://github.com/patchy631/ai-engineering-hub).
