國際經濟研究所(Graduate Institute of International Economics)
課程名稱(英文)
Modern Big Data Analysis
課程代碼
5105867_01
授課教師：
簡廷軒
學分數
3
必/選修
選修
開課年級
1
先修科目或先備能力：
It is recommended that students have a basic knowledge of statistics and programming logic.
建議學生具備基本的統計學及程式邏輯知識。
課程概述：
Students will gain an understanding of what insights big data can provide through hands-on experience with the tools and systems used by big data scientists and engineers. This course guided through the basics of using Hadoop with MapReduce, Spark, Pig and Hive by following along with provided code, students will experience how one can perform predictive modeling and leverage graph analytics to model problems.
本課程將針對現今大數據資料分析之理論基礎及應用進行介紹，以及透過實際操作大數據分析所需使用的工具和系統，了解如何將分析結果與實務結合。本課程將提供範例程式碼並使用 Hadoop 與 MapReduce、Spark、Pig 和 Hive 等基礎工具，體驗如何執行建模和利用其分析大數據資料。
An introduction to one of the most common frameworks, Hadoop, that has made big data analysis easier and more accessible -- increasing the potential for data to transform our world
6
2
Big Data Modeling and Management Systems
In this course, students will experience various data genres and management tools appropriate for each.
6
2
Big Data Integration and Processing
Retrieve data from example database and big data management systems.
Describe the connections between data management operations and the big data processing patterns needed to utilize them in large-scale analytical applications.
8
2
Machine Learning Based on Big Data
An overview of machine learning techniques to explore, analyze, and leverage data.
8
2
Graph Analytics for Big Data
Model a problem into a graph database and perform analytical tasks over the graph in a scalable manner, and apply these techniques to understand the significance of data sets for final projects.
6
2
Final Project- Case Study
Build a big data ecosystem using tools and methods form the earlier courses in this specialization.