1. Introduction to Data Analysis and Data Mining 2. Machine learning with numeric techniques 3. Numerical learning 4. Evaluation of Machine Learning Models 5. Attribute analysis 6. Methodology of data mining projects 7. Introduction to other advanced techniques (combination, SVM , Fuzzy systems, GAs)

Seminars and lectures supported by computer and audiovisual aids. Practical learning based on cases and problems, and exercise resolution. Individual and group or cooperative work with the option of oral or written presentation. Individual and group tutorials to resolve doubts and queries about the subject. Internships and directed laboratory activities.