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Data Mining (데이터마이닝)
Course description: Data mining is the area that study techniques to capture meaningful informations which reside in the vast and complex data. In this lecture, students learn basic techniques of data mining and shall be familiar with the use of techniques by means of several real problems. Specifically, dimension reduction, multiple and logistic regression, decision trees, K-nearest neighbors, neural networks, Baysian classifier, classification trees, discriminant analysis, association rules and cluster analysis are topics to be covered.
Textbook: Data Mining for Business Intelligence, 2nd ed. (2010) G. Shmueli, N.R. Patel, and P.C. Bruce (Wiley)
Topics:
1 Introduction
2 Overview of the Data Mining Process
3 Data Visualization
4 Dimension Reduction
5 Evaluating Classification and Predictive Performance
6 Multiple Linear Regression
7 k-Nearest Neighbors
8 Naive Bayes
9 Classification and Regression Trees
10 Logistic Regression
11 Neural Nets
12 Discriminant Analysis
13 Association Rules
14 Cluster Analysis
and some more advanced topics (Support Vector, Hidden Markov Model, etc.)
Prerequisite: Basic probability and statistics course.
Glossaries: Students will be asked to use some softwares such as MATLAB, SAS,and Excel for some of their homework problems.
Stochastic Modelling (확률모델링)
Textbook : Handouts
References : 확률과정론(청문각) 허 선 역
Topics 1. Elementary probability theory review (total probabilities, random variables, distribution functions, conditional expectations, random sums, etc.)2. Fitting data to distributions, test of goodness-of-fit3. Exponential distribution and Poisson process4. Discrete-time Markov chain and cost models5. B-D Process, continuous-time Markov chain and cost models6. Queueing theory and applications (characteristics, M/M/-type queues, M/G/1, Jackson’s queueing network)7. Probabilistic inventory theory (single/multiple period, with/without setup cost)8. Markov decision process, optimal stopping times9. Hidden Markov models (if time permits)
Students will be asked to utilize an Excel program "QtsPlus" for their homework problems.There is a homepage for this class. I will use it frequently by posting homeworks, notices, supplementary materials and Q&A. You are strongly encouraged to review after class not to get lost.
Service Management Engineering (서비스운영공학)
Course Summary: As the importance of service area in macro economy grows many studies are concentrated on the issues regarding efficient design and operation of service area. In this lecture we analyze the service systems accompanying queueing delays and develop and evaluate the methods to improve and/or maintain various performance measures such as waiting time by means of engineering tools. Main topics include: data gathering in queueing systems, arrival process analysis, steady-state analysis, non-stationary system analysis, tools for improving performance, service order and arrangement of service stages.
교재 : (Hall, Randolph. Queueing Methods for Services and Manufacturing. Prentice-Hall, 1991.
Recommended Prerequisite: INE344 (Introduction to Stochastic Modelling)
In-class Lecture Topics :
I. Introduction
II. Observation and Measurement
III. The Arrival Process
- Poisson process/Poisson distribution/ Goodness-of-fit (qualitative, statistical)/ Parameter estimation
V. Steady-state Analysis
- M/M/, M/G/, G/G/ / System performances in the steady-state
VI. Nonstationary Arrivals
- Fluid approximation
VII. Reducing Delay by Changes in the SVC Process
- Various methods to reduce service time(descriptively)/ Cost trade-off
VIII. Reducing Delay by Changes in the ARR Process
- Various mehtods to reduce waiting time by appointment(descriptively)/ Pricing
IX. Queue Discipline
- Effect of service disciplines on the performance/ FCFS, LCFS, SST, EDD, SWST, hybrid, and much more
X. Queueing Networks
- Fluid approximation
XI. Queue Design
- Queueing space, queue layout
Management of Technology (글로벌기술경영)
Course Summary: 공학도들이 기업의 CEO, 나아가 사회의 지도자가 되기 위해서는 다양한 경영기능과 역할을 이해하고 실행할 수 있는 다기능 경영자가 되어야 한다. 이를 위해 본 강의에서는 산업구조와 기업구조, 경영조직의 구조와 설계, 경영전략의 분석과 기획, 경영프로젝트의 개발과 통제, 재무제표와 재무분석 등을 학습한다.
교재 : (공학도를 위한) 기술과 경영, 박용태 저, 생능출판사
강의내용 :
1. 기술과 경영 서론 - 공학도와 CEO - 공학과 경영학
2. 산업구조와 기업구조 - 산업의 정의와 구조 - 기업의 형태와 구조
3. 경영조직의 구조와 설계 - 기업조직의 설계와 유형 - 연구개발 조직의 설계 - 서비스 조직의 설계
4. 경영전략의 분석과 기획 - 경영전략의 정의와 배경 - 경영전략의 구조 - 전략분석의 틀
5. 경영프로젝트의 개발 - 기술예측과 기술 로드맵 - 신기술/신제품의 기획
6. 경영프로젝트의 경제성 평가 - 경제성 평가의 기본개념과 내용
7. 경영 프로젝트의 통제 - 경영프로젝트 일정관리 기법
8. 재무제표와 재무분석 - 회계시스템 - 재무제표 - 재무분석
9. 원가관리 - 원가회계의 기본과 실무 - 원가관리
10. 상업화와 마케팅 - 상업화 활동 - 마케팅 - 하이테크 마케팅 - 전자상거래 - 고객관계관리
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