COURSE #SRO-644
MODERN DATA MINING:
Concepts, Methodology, and Applications
... comprehensive introduction to the field of data mining covers the basic principles as well as the most advanced techniques employed in commercial and military applications in DoD use today…
Rapidly evolving technologies enable the cost-effective collection and storage of massive amounts of data. The ‘knowledge’ content within these data present organizations with new, historically unmatched, opportunities to enhance their decision-making processes. Data Mining provides the power to discover and model the relevant knowledge (i.e., patterns and relationships) residing in the data. This essential component of the knowledge discovery process augments other capabilities (e.g., OLAP queries and data visualization) in the organizations’ decision support system architectures.
This course provides an introduction to the principles, processes, and techniques employed by data mining for discovering the underlying relationships in large amounts of data. Topics covered include the data mining process, data preparation, and model development/validation, as well as a number of pattern recognition techniques. Techniques covered include the traditional statistical pattern recognition, as well as the more recent artificial neural networks, decision trees, genetic algorithms, and hybrid systems. Concepts introduced are supported by extensive examples of the techniques used in commercial and military applications solving practical data mining problems.
Applications and benefits:
You will benefit by enhancing your understanding of the:
- Data Mining principles and terminology
- Data Mining process and general implementation
- Data Mining problem classes and approaches to address them
- How to conduct data preparation and segmentation
- Data Mining techniques and implementations.
- Results analysis, interpretation, and validation
- Commercially available tools for data mining
Who should attend:
This course, focusing on the concepts and techniques utilized in effective data collection, analysis and exploitation, offers a solid foundation in the science of Data Mining. The powerful techniques of Data Mining serve sophisticated commercial and military applications, both discussed in depth. The information presented here serves as an invaluable resource for managers, analysts, consultants, scientists, engineers, data mining practitioners, and all others who are interested in applications of leading-edge data mining techniques towards improvement of decision-making processes. This course does not have prerequisites; however, a familiarity with large databases would be helpful.
Course Outline:
- Introduction to Data Mining
- Typical Data Mining Problems
- The Data Mining Process
- Model Evaluation Framework
- Statistical Pattern Recognition
- Estimation Problems
- Linear Regression
- Estimation Demonstration
- Classification Problems
- Logistic Regression
- K Nearest Neighbors
- Classification Demonstration
- Introduction to Artificial Neural Networks
- Introduction to Artificial Neural Networks
- Artificial Neuron Model
- Neural Network Architectures and Supervised Learning
- Neural Network Model Development
- Data Representation
- Variable/Feature Selection
- Data Segmentation
- Network Development
- Training and Performance Evaluation
- Troubleshooting
- Estimation, Classification and Time Series Forecasting with Neural Networks
- Estimation Demonstration
- Classification Demonstration
- Time Series Demonstration
- Unsupervised Clustering
- Self Organizing Maps (theory, architecture, algorithm)
- Unsupervised Clustering Demonstration
- Decision Trees
- Recursive Partitioning Concept
- Classification Demonstration
- Additional Topics
- Genetic Algorithms
- Multiple Classifier Systems (aka Ensembles)
- Hybrid Systems
- Commercial Data Mining Software Vendors and Tools
- Data Mining Resources
Text:
Attendees will depart with a binder full of slides, supporting notes, and data mining references.
About the Instructor
Dr. William Crocoll is a Senior Principal Engineer in the Integrated Technology Solutions Unit of ITT Industries’ Advanced Engineering and Sciences Division. He has taught data mining and artificial intelligence courses, workshops, and seminars to over 500 Department of Defense analysts while a professor at the U.S. Army Logistics Management College, as well as knowledge-based systems and data mining techniques to graduate students while an adjunct professor for the Florida Institute of Technology. His practical experience includes developing data mining solutions for predicting potential challenges to U.S. global security interests, prioritizing advertising leads, classifying vehicles using multi-sensor data, and forecasting resource leveraging for a community service organization. He is currently working on a number of data mining/fusion efforts for the U.S. government.
Details:
Course: SRO-644 Duration: 3 Days FEE: $1,499 CEUs: 2.16
Please direct any additional inquiries regarding our courses to Zygmond Turski, Program Director, by e-mail, FAX: (636) 273-4955 or TELEPHONE: (636) 273-9608.
Call toll free 1-800-683-7267 from anywhere in the Continental U.S. or CANADA.
Last modified April 6, 2008.
