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Data Mining (Summer 2008)

Welcome to CMPSC 54: Data Mining

As described in the student handbook:

This course is designed to familiarize individuals with current and emerging data mining technologies using the Internet, database software, and other application software packages as needed for project completion. Data mining knowledge topics will include the process of model building. Students will create a representative model based on an existing dataset to help understand trends, patterns, and correlations, as well as forming predictions based on historical outcomes. Students will be introduced to the tools and technologies needed to research and analyze data, resulting in a strategic decision making, marketing plan development, goal setting and identifying business opportunities. (CSU)

Credit may be earned for either CMPSC 54 or BUSAD 54, but not both.

Required Text:
  • Data Mining, Second Edition, Second Edition : Concepts and Techniques (The Morgan Kaufmann Series in Data Management Systems) by Jiawei Han, Micheline Kamber
Recommended Texts:
  • Data Mining: Practical Machine Learning Tools and Techniques, Second Edition, Ian H. Witten, Eibe Frank
  • Super Crunchers: Why Thinking-by-Numbers Is the New Way to Be Smart, Ian Ayres

Handouts:
  • Statistics Primer
  • Database Primer

Schedule:

Section 1 Introduction

Wk 1: Introduction

Wk 2: Uses of Data Mining

Wk 3: Abuses of Data Mining (data dredging)

 

Section 2 Data Mining Essentials

Wk 4: Measures (Metrics, Indicators)

Wk 5: Data Preparation

Wk 6: Classification [Predictive]

Wk 7: Clustering [Descriptive]

Wk 8: Association Rule Discovery [Descriptive]

Wk 9: Sequential Pattern Discovery [Descriptive]

Wk 10: Regression [Predictive] & Deviation Detection [Predictive]


Section 3: Applications

Wk 11: Web Mining 

Wk 12: Business Intelligence (BI) 

Wk 13: Customer Relations Management (CRM)

Wk 14: Fraud Detection & Law Applications

Wk 15: Bioinformatics & Other Scientific Applications 

Wk 16: Finals

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  • 01.ppt   2692k - Apr 10, 2008 4:33 PM by John Taylor (v1)
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