將資料科學所常用的各類「模型」之相關數學、統計知識做一個通盤的介紹，以俯視的角度，來抓住各領域常用模型之間的關聯，並探討現實中不同問題的分析方式。然後將它們整合應用到「品管統計方法」（Statistical Quality Control; SQC），以及以「數據驅動」為核心策略的「網路產品生命週期管理」等課題上。It will provide a comprehensive introduction to the relevant mathematical and statistical knowledge of various "models" commonly used in data science. From a bird's-eye view, it will grasp the relationship between commonly used models in various fields and explore the analysis methods of different problems in reality. Then integrate them and apply them to topics such as "Statistical Quality Control (SQC)" and "Internet Product Lifecycle Management" with "data-driven" as the core strategy.
王心薇譯, “資料科學的建模基礎：別急著coding！你知道模型的陷阱嗎？”, 旗標出版社, 2021/06.
Translated by Wang Xinwei, "Basics of modeling in data science: Don't rush to coding! Do you know the traps of models?", Banner Press, 2021/06.
| 評分項目 Grading Method | 配分比例 Grading percentage | 說明 Description |
|---|---|---|
| 平時出席平時出席 usually attend |
20 | 著重課堂上參與提問及討論。 |
| 報中報告報中報告 report |
30 | 以微軟Excel工具，來分析指定的品管作業。 |
| 期末報告期末報告 Final report |
50 | 以知名的「網路產品」，例如：Netflex、Google、… 為研究對象，蒐集研讀從網路及文獻上關於本課程 “以「數據驅動」為核心策略的「網路產品生命週期管理」” 所探討的各項議題。 |
