1. Introduction to Data

2. Data Preprocessing

3. Measures of Similarity and Dissimilarity

4. Exploring Data

5. Classification: Basic Concepts, Decision Trees

6. Classifiers: Nearest-Neighbor, Bayesian, ANN, SVM

7. Ensemble Methods and Class Imbalance Problem

8. Association Analysis

9. Cluster Analysis

10. Anomaly Detection

Total hours: 50