Programming (preferably Python)

General: 1. Analysis and synthesis skills 2. Planning and organization skills 3. Problem solving skills 4. Team work skills 5. Capacity to apply theoretical concepts into practical problems 6. Critical Reasoning skills Knowledge: 1. Knowledge about main Artificial Intelligence (AI) techniques and concepts. 2. Knowledge about the application of the different AI techniques in different areas, such as business, banking or finance. 3. Knowledge about the complexity in implementing intelligent solutions in real environments. Instrumental: 1. Designing intelligent systems to solve practical problems. 2. Critical analysis of real-life problems. 3. Using specific tools to develop intelligent systems. Attitude: 1. Creativity. 2. Quality aspects. 3. Motivation. 4. Seeking solutions to new problems.

1.- Introduction to Big Data 2.- Biga Data Methodology 3.- Big Data Classic Techniques 4.- Supervised Learning and Classifiers 5.- Regression trees and neural networks. 6.- Other approaches

Learning activities: * Theoretical lectures: Mainly oriented to the acquisition of the theoretical knowledge of the subject' competences * Practical lectures: Mainly oriented to problem solving. Practical activities will include (preferably in Python) programming and the use of a public dataset. * (online or onsite) Personal Tutoring (asked by email in advance) Methodology: * Oral lectures in classroom * Problem solving