本課程目標是讓學生能夠了解AI大數據相關技術與議題，包含數位匯流的概念與趨勢，探討不同領域之間異質資料整合的方法，以及生成式AI應用與介紹，數據資料倉儲到資料分析技術。並延伸介紹數據科學應用領域社群計算與社群媒體分析方法，並提供大數據應用實例探討模擬並進行小組專題製作，藉以加強學生在大數據時代的實作能力，讓學生實際接觸AI與大數據應用。
The purpose of this course is to allow students to understand AI data-related technologies and issues, including the concepts and trends of digital flow, explore methods for integrating different data between different domains, as well as generative AI applications and introductions, and transfer data to data analysis technology. It also introduces the community computing and social media analysis methods in the field of data science application, and provides large-data application example exploration simulation and group topic production to enhance students' practical ability in the big data era and allow students to actually access AI and big data applications.
1. [Coursera] 大數據分析：商業應用與策略管理 (Big Data Analytics: Business Applications and Strategic Decisions)
2. [Book] O'Neil, Cathy,Schutt, Rachel,Doing data science :Sebastopol, CA O'Reilly, 2014.
3. [Book] McKinney, Wes. Python資料分析 第三版 (Python for Data Analysis, 3rd Edition). Translated by 賴屹民, 歐萊禮出版社, 2023.
1. [Coursera] Big Data Analytics: Business Applications and Strategic Decisions
2. [Book] O'Neil, Cathy, Schutt, Rachel, Doing data science :Sebastopol, CA O'Reilly, 2014.
3. [Book] McKinney, Wes. Python Data Analysis Third Edition (Python for Data Analysis, 3rd Edition). Translated by Qi Yimin, Ole Lerong Publishing House, 2023.
| 評分項目 Grading Method | 配分比例 Grading percentage | 說明 Description |
|---|---|---|
| 平時成績(出席、參與及作業)平時成績(出席、參與及作業) Regular achievements (attendance, participation and work) |
40 | |
| 期末論文報告/專題發表期末論文報告/專題發表 Final commentary report/project release |
60 |
