5517 - 生成式AI應用系統與工程

Generative AI Application Systems and Engineering

教育目標 Course Target

本課程以「⽣成式 AI 應⽤系統」開發為核⼼，帶領學⽣從需求分析、系統設計，到實作與部署，完成⼀個⽣成式 AI Web服務。內容涵蓋軟體⼯程SDLC、前後端技術、資料流程與⼯作流、開源CI/CD與 MLOps/LLMOps⼯具、AWS 雲端環境、分散式 AI Infra、LLM 微調與 local LLM 評測、Agent ⼯作流與 MCP/ADK/agent-to-agent架
構、LiteLLM/OpenRouter 等模型代理⼯具，以及 token 經濟學、Prompt 優化、多輪對話設計、幻覺減少與 LLM 資安議題。
學⽣將透過⾄少六次程式作業與期末專題，實作⼀個具完整⼯程思維的⽣成式AI應⽤系統

This course takes "generative AI application system" development as the core and leads students to complete a generative AI web service from demand analysis, system design, to implementation and deployment. The content covers software engineering SDLC, front-end and back-end technology, data flow and workflow, open source CI/CD and MLOps/LLMOps tools, AWS cloud environment, distributed AI Infra, LLM fine-tuning and local LLM evaluation, Agent workflow and MCP/ADK/agent-to-agent framework
Model agent tools such as structure, LiteLLM/OpenRouter, as well as token economics, prompt optimization, multi-round dialogue design, illusion reduction and LLM security issues.
Students will implement a generative AI application system with complete engineering thinking through at least six programming assignments and final projects.

參考書目 Reference Books

1.講義、程式碼⽰例、AWS 教材
2.MCP、LLMOps、Ray 等官⽅⽂件

1. Lecture notes, program code examples, AWS teaching materials
2. Official documents such as MCP, LLMOps, and Ray

評分方式 Grading

評分項目
Grading Method		 配分比例
Percentage		 說明
Description
HW 1-6：10% each HW
HW 1-6：10% each HW
 60
Final Project：40%
Final Project：40%
 40 ○ Ranking based on 系統架構圖（含微服務拆分、Agent workflow）、服務流程圖與 API 設計、Demo Presentation and Slides、GitHub Source and Technical Report

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課程資訊 Course Information

基本資料 Basic Information
  • 課程代碼 Course Code: 5517
  • 學分 Credit: 0-3
  • 上課時間 Course Time:
    Wednesday/5,6,7,8[遠距課程]
  • 授課教師 Teacher:
    莊坤達
  • 修課班級 Class:
    共選修3,4,碩博1,2(工學院開)
  • 選課備註 Memo:
    教育部補助臺灣大專院校人工智慧學程聯盟，開設學校：成功大學，同步遠距上課時間：週三14:00~17:00。
選課狀態 Enrollment Status
目前選課人數 Current Enrollment: 22 人
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