校際選修

115-1 選課時程

進行中

  • 初選第一階段 6/15/2026
  • 初選第二階段 6/22/2026
  • 校際選修 8/24/2026
  • 初選第三階段 8/31/2026
  • 開學後加退選 9/7/2026
  • 逾期加退選 9/21/2026
選課資源

資料探勘與商業智慧

Data mining and Business Intelligence

學期
111-2
學分
3 學分
當期課號
537712
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
週三
A
18:30–19:20
資料探勘與商業智慧
M101
3 節連堂
B
19:30–20:20
C
20:30–21:20

* 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Introduction to machine learning and data mining
第 3 週Classification I
第 4 週Classification II
第 5 週KNN and Kmeans
第 6 週Association Rules
第 7 週Clustering
第 8 週Anomaly Detection
第 9 週Mid-term Exam
第 10 週Service Design I
第 11 週Service Design II
第 12 週Business Plan Writing
第 13 週Case Study I (Ubereats)
第 14 週Case Study II (Tesla)
第 15 週Case Study III (Post-covid-19 business intelligence)
第 16 週Business Intelligence Final Report
第 17 週On-line Seminar
第 18 週On-line Seminar
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