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This text is written at an introductory level and provides real world problem analysis and practical examples as well as data mining theory to enable students to apply the concepts of data mining outside the classroom. This mix of theory and practical application makes this text directly suitable for a wide variety of undergraduate disciplines such as business computer science, students engineering, economics, statistics, marketing, information systems and information technology Table of Contents 1. Fundamentals of Data Mining 2. Data Processing and Data Warehouse 3. WEKA: An Attractive Data Mining Tool 4. The Classification Task 5. Artificial Neural Networks and Support Vector Machines 6. Model Evaluation Techniques 7. Association Rule Mining 8. The Clustering Task 9. The Estimation Task 10. Mining of Time Series 11. Text and Web Mining 12. Privacy, Security and Ethical Issues in Data Mining