Data mining course by Metus Systems

Frank Hoffmann (
Thu, 25 Mar 1999 20:22:14 +0100 (MET)

Berkeley Initiative in Soft Computing (BISC)
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April 20-21, 1999
Corporate Software Training Center
Research Triangle Park, NC


Conducted by
Metus Systems
1289 N. Fordham Blvd Suite A312
Chapel Hill, NC 27514
(919) 968-3399

A complete course in how to structure data mining projects, the nature of
the knowledge discovery methodology, how to select the proper tools and
methods for various kinds of projects (supervised, unsupervised, and
hybrid). The problem with data - cleaning, transforming, structuring, and
organizing data. A detailed analysis of conventional approaches and a
complete discussion and analysis of machine intelligence approaches such as
fuzzy logic, neural networks, and genetic algorithms. Learn how to match
tools and techniques with mission objectives. Learn about dangers and
pitfalls. Guidelines for managing, budgeting, controlling, and completing a
data mining project. Learn how to combine private, corporate, Intranet, and
public (Internet and Web-based) data sources. Case studies, histories, and
examples. Hands-On computer sessions using data mining tools to explore
data bases and spread sheets.

You will receive the complete slides and workbook, a Data Mining
Methodology Checklist and Review Manual, Shareware and demo versions of
popular data mining software, and a fully functional copy of The Fuzzy data
Explorer, a Windows/95/NT point-and-click Rule Discovery system with an
integrated, inference engine and graphical (visualization) tool set.

Day One
What is data Mining?
History and Evolution
Supervised and Unsupervised Data Mining
Objectives and Models
Pattern Recognition
Function Estimation
Techniques and Methods
Current Trends
The Future
Some Case Histories
A Manager's Guide to Technology
Statistical Inferences
Probability and Baysian Implications
Rule Induction
Machine Reasoning Technologies
Expert Systems
Neural Networks
Fuzzy Logic
Genetic Algorithms
Chaos Theory (Nonlinear Dynamics)
Finding, Using and Exploiting Data
Data Sources
Conventional Database
The Data Warehouse and Data Marts
Spread Sheets and Files
Corporate Intranets
Public Data Sources and the Internet
What exactly is Data?
The Problems with Data
Understanding the nature of Information and Knowledge
Organizing your project to recognize Knowledge
Analyzing data: Using SQL and FuzzySQL to identify patterns
Matching Tools to Objectives
Models and Objectives
Statistical Models
Mathematical Models
Partitioning and Classification Models
Rule Induction
Commercial Data Mining Tools
Freeware and Shareware Tools
Build-Your-Own Tools
Hands-On Session #1.
Review of Commercial tools
Data Mining a Project Assessment database
Connecting to spreadsheets and databases

Day Two

The Data Mining Methodology
The Phases in a data Mining Project
The Nature of Dependent and Independent variables
Establishing clear project objectives
Acquiring and Cleaning data assets
Finding and Specifying Outcome (Decision) Variables
Discovering Behavior Patterns - Training a Model
Validation and Tuning
Adaptive Feed-Back
Deploying and Monitoring a Production Model
Combining a Methodology with a Project Plan
Managing Uncertainty through estimation techniques
Setting realistic goals and project scopes
Skills Requirements
Prototyping and Protocycling
Managing Expectations
Budgeting and Resource allocation
What to tell your management and when
Use of outside consultants, internal consultants
Evaluating tools
Danger signs of a project in trouble
How to avoid trouble
Hands-On Session #2
A simple data mining project
Team competition to design and build the project
Using Fuzzy Data Explorer to create a production model

*************************** ***************************
Earl D. Cox AUTHOR:
Wandering Epistemologist "The Fuzzy Systems Handbook" (1994)
Phrenologist-for-Hire "Fuzzy Logic for Business and Industry" (1995)
Foreteller of the Past "Beyond Humanity: CyberEvolution and Future Minds"
(919) 859-1736 (vox) (1996, with Greg Paul, Paleontologist/Artist)
(919) 851-3525 (fax) "The Fuzzy Systems Handbook, 2nd Ed." (1998)
"Fuzzy Tools for Data Mining" (due Summer, 1999)
******* No Good Deed Ever Goes Unpunished (Mark Twain/Abraham Maslow) ******

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