大數據分析

臺北科技大學 115-1 學期課程，課號 366648。

• 學期：115-1
• 授課教師：王正豪、鄭麗珍
• 學分：3
• 選修
• 上課時段：週二 2、3、4 節

課程大綱

This course introduces the methods and applications of big data analytics. The topics include big data management, data mining techniques, big data platforms, and project implementation and presentation. Students are expected to learn the concepts of big data analytics techniques, and their applications and future trends in different case studies.

課程進度

Part I: Data mining concepts (6 wks) 1. Introduction to big data concepts & data preprocessing (1 wk) 2. Frequent pattern mining (2 wks) 3. Data classification (2 wks) 4. Data clustering (1 wk) Week #8: Midterm exam (1 wk) Note: I'm responsible for the first part in 6 weeks (Week 2-7).

評量方式

For Part I: - Homework assignments: ~60% - Midterm exam: ~40% The percentage of your score in Part I will be around 1/3 of the total score. It's roughly related to the number of weeks, and will be confirmed with Prof. Cheng.

教材

【遵守智慧財產權觀念，請使用正版教科書，不得使用非法影印教科書】 使用外文原文書：是 - Textbook: Jiawei Han, Micheline Kamber, and Jian Pei, Data Mining: Concepts and Techniques, 4th edition, Morgan Kaufmann, 2022. - References: 1. Jimmy Lin and Chris Dyer, Data-Intensive Text Processing with MapReduce, Morgan & Claypool Publishers, 2010. 2. Holden Karau, andy Konwinski, Patrick Wendell, and Matei Zaharia, Learning Spark: Lightning-fast data analysis, O'Reilly, 2015. 3. Recent academic papers, tutorials, and slides.