資料探勘與商業智慧

Data mining and Business Intelligence

學期

112-2

學分

3 學分

當期課號

537711

永久課號

MGIF30078

開課單位

資訊管理與財務金融系財務金融碩博士班

授課教師

黃思皓

校區

光復

類別

選修

上課時間表

節	週三
8 16:30–17:20	資料探勘與商業智慧 M101 3 節連堂
9 17:30–18:20
A 18:30–19:20

* 根據陽明交大上課時間表所列

概述

With the rapid development of artificial intelligence and big data analytics techniques, several innovative applications and novel business model are proposed to improve the daily operations of enterprises and business strategies. This course includes two major parts: (1) Data Mining: The courses in the first half semester introduces the theory and practices of data mining techniques. Data mining is an interdisciplinary research field which involves machine learning, statistics, and database management. It focuses on the pattern extraction and knowledge discovery from large data sets. (2) Business Intelligence: The remaining courses will let the students understand the emerging issues about business intelligence(BI). BI comprises the strategies and technologies used by enterprises for the data analysis of business information. Several important tools, including data visualization, report automation, data-driven decision making, will be discussed with the lectures, case study, and oral presentation.

先修科目

Fundamental programming skills

評分方式

Midterm exam 40% Class participation 10% Homeworks, group presentation and Final project 50%

課程大綱

Business Intelligence
Data mining

週次計畫

週次	主題
第 1 週	Course Introduction
第 2 週	No classes on 228 Peace Memorial Day
第 3 週	Introduction to machine learning and data mining
第 4 週	Know your data
第 5 週	Data processing
第 6 週	Mining Frequent Patterns, Association and Correlations
第 7 週	No classes during the Inter-school Activity Week
第 8 週	Clustering, KNN, and K-means
第 9 週	Mid-term exam
第 10 週	Classification and artificial neural networks
第 11 週	Recommendation system
第 12 週	Recommendation system
第 13 週	Oral presentation and case study I
第 14 週	Oral presentation and case study II
第 15 週	Oral presentation and case study III
第 16 週	Oral presentation and case study IV

教科書

Han, J., Pei, J., & Tong, H. (2022). Data mining: concepts and techniques. 3/e, Morgan kaufmann.

Office Hours

地點: Room 418, Management Building I
時間: by appointment
聯絡方式: szuhaohuang@nycu.edu.tw