課程大綱

課程資訊

課程名稱

大數據理論及實務應用
Big Data Applications and Theories

開課學期

105-2

授課對象

理學院數學系

授課教師

林大溢

課號

MATH5037

課程識別碼

221 U6940

班次

學分

3.0

全/半年

半年

必/選修

選修

上課時間

星期三2,3,4(9:10~12:10)

上課地點

天數102

備註

總人數上限：80人

Ceiba 課程網頁

http://ceiba.ntu.edu.tw/1052MATH5037_

課程簡介影片

核心能力關聯

本課程尚未建立核心能力關連

課程大綱

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課程概述

這個世紀, 當我們生活在大數據資料時代，身為台大學生當然需要且必要知道，不論文字、數字、照片、視訊、音訊、座標、時間、速度、網際網路、行動網路等交織成的數位大數據資料空間，我們可以做什麼？我們應該了解什麼？這是我們這門大數據導論的目標。

課程目標

修完此門課的同學將能夠：
1. 舉出真實世界中大數據的實例和描述大數據的三個關鍵資料來源
2. 運用Google big data tools 發現問題，找出可能的線索與預測
3. 解釋大數據的6V
4. 了解大數據分析的標準五步驟的使用方法
5. 辨別問題是大數據類型或不是？
6. 明瞭大數據計算機模型與程式語言架構：scalable big data analysis.

課程要求

準時出席不缺課
完成指定閱讀
期中與期末上台報告

預期每週課後學習時數

Office Hours

另約時間備註：前一週預約 Wednesday 12:30-13:20

指定閱讀

1. Did you know?: 25 facts about big data
2. What Launched the Big Data Era?
3. Applications: What Makes Big Data Valuable?
4. Saving Lives With Big Data
5. Using Big Data to Help Patients
6. Machine-Generated Data: It's Everywhere and There's a Lot!
7. Machine-Generated Data: Advantages
8. Big Data Generated By People: The Unstructured Challenge
9. Big Data Generated By People: How Is It Being Used?
10. Organization-Generated Data: Structured but often siloed
12. Organizaton-Generated Big Data: Benefits
13. Integrating Diverse Data
14. Characteristics of Big Data: Volume, Variety, Velocity, Value, Valence
15. Five P's of Data Science
16. Getting Value Out of Big Data
17. Building a Big Data Strategy
18. The Five P's of Data Science
19. Asking the Right Questions
20. Steps in the Data Science Process: Acquiring, Exploring, Preprocessing, Analysis, Communicating results, turning insights into action
21. What is a Distributed File System?
22. Scalable Computing Over the Internet
23. Programming Models for Big Data
24. Big data tools provided by Google

參考書目

待補

評量方式
(僅供參考)

No.	項目	百分比	說明
1.	期中簡報及上台報告	35%	1.每位學生須email一份powerpoint 2.老師將抽10位同學上台報告
2.	期末簡報及上台報告	45%	1.每位學生須email一份powerpoint 2.老師將抽10位同學上台報告
3.	期末報告及課堂表現	20%	1.每位學生須email一份term report in word format 2.課堂提問與參與討論

課程進度

週次	日期	單元主題
第1週	2/22	Introduction to the course Discussion: Why are you taking this class?
第2週	3/01	What launched the Big Data era? What makes big data valuable? Discussion: What application area interests you?
第3週	3/08	Saving lives with Big Data Using Big Data to Help Patients Meltwater helping Danone 25 facts about big data
第4週	3/15	Google tools for Big Data
第5週	3/22	What Launched the Big Data Era? What Makes Big Data Valuable? The Key: Integrating Diverse Data
第6週	3/29	Where Does Big Data Come From? Machine-Generated Data Big Data Generated By People Organization-Generated Data Open Data by Gov and NPO discussion: Who are you providing data to?
第7週	4/05	Spring break
第8週	4/12	Characteristics Of Big Data Characteristics of Big Data - Volume Characteristics of Big Data - Variety Characteristics of Big Data - Velocity Characteristics of Big Data - Veracity Characteristics of Big Data - Valence The Sixth V: Value
第9週	4/19	Big Data Case study : Cyber Security
第10週	4/26	Mid-term presentation : Writing Big Data questions
第11週	5/03	Guest speaker: topic related to Big data
第12週	5/10	Asking the Right Questions Steps in the Data Science Process Step 1: Acquiring Data Step 2-A: Exploring Data Step 2-B: Pre-Processing Data Step 3: Analyzing Data Step 4: Communicating Results Step 5: Turning Insights into Action Discussion: Building a Team
第13週	5/17	Getting Value out of Big Data Building a Big Data Strategy Five Components of Data Science Discussion: Thinking more deeply about the Ps
第14週	5/24	Cloud computing and Ecosystem
第15週	5/31	此次課程移到 6/14上課 (Big Data cases study in Taiwan)
第16週	6/07	term presentation : Answers to your Big Data questions
第17週	6/14	1. 補5/31課程 2. Hand-out term report