2012年10月《哈佛商業評論》（Harvard Business Review）將能透過電腦演算分析資料、解讀意義的資料科學家（data scientist）稱為「21世紀最性感的工作」（Data Scientist: The Sexiest Job of the 21st Century），這是因應大數據(Big Data)、或巨量資料潮流所造就的新職種中，最具代表性的。
《哈佛商業評論》曾為資料科學家下了一個定義：「資料科學家是懂得從今日如海嘯般非結構化資訊中，撈出重要商業問題解答的一群人。」事實上，資料科學家不只是要像哥倫布般，在茫茫大海中打開探照燈，找出有用的資料，還要如偵探小說家愛倫坡一樣，審視手上的資料，推理出問題的答案。
緣此，本課程旨在帶領公共事務碩士在職專班學生進入大數據、問題解決與決策分析的理論與實務殿堂，提供學生一場域，藉由R程式語言為工具、以議題為導向、結合跨領域專長的專題形式，學習有關大數據資料科學與循證(evidence-based)公共決策結合的基礎概念、與相關技術等，也為同學將來成為資料科學家做準備。課程內容主題包括：政府開放資料（Open Data）、大數據與資料分析（Big Data Analysis）、R語言、文字資料探勘與SAS Enterprise Miner、以及互動式資料視覺化Tableau等軟體的應用。
The October 2012 "Harvard Business Review" will be the most representative of the new jobs created by computer calculations and data scientists who can analyze data and interpret meanings through computer calculations.
"Harvard Business Review" once gave a definition for data scientists: "Data scientists are a group of people who know how to answer important business questions from today's non-structured information like a sea." In fact, data scientists should not only open search lights in the vast ocean like Colembo and find useful information, but also examine the data in their hands and infer the answers to questions like the detective novelist Love Lenpo.
In this way, this course aims to lead public affairs students in professional courses into the theories and practice halls of data, problem solving and decision analysis, providing students with a field, using R program as a tool, using question-oriented, and combining cross-border The specialized form of the field, learning basic concepts and related technologies that combine large data science and evidence-based public decisions, is also a preparation for students to become data scientists. The course content topics include: Open Data, Big Data Analysis, R language, text data exploration and SAS Enterprise Miner, and the application of software such as interactive data visualization Tableau.
1. R語言：邁向Big Data之路。作者：洪錦魁，蔡桂宏。出版社：上奇資訊。出版日期：2015。
2. 中、英文書籍與期刊論文。
1. R language: The road to Big Data. Author: Hong Qikui, Cai Guihong. Publisher: Shangqi Information. Publication date: 2015.
2. Chinese and English books and journals.
| 評分項目 Grading Method | 配分比例 Grading percentage | 說明 Description |
|---|---|---|
| 上課參與和討論上課參與和討論 Participate in and discuss in class |
10 | |
| 平時讀書報告與作業平時讀書報告與作業 Reading reports and operations on the fly |
20 | |
| 個人專題1（口頭5%；網頁25%）個人專題1（口頭5%；網頁25%） Personal topic 1 (5% on the mouth; 25% on the web) |
30 | |
| 個人專題2（口頭10%；網頁30%）個人專題2（口頭10%；網頁30%） Personal topic 2 (10% mouth; 30% web page) |
40 |
