Checking date: 29/05/2023

Versión en español

Course: 2023/2024

Big Data
(17484)
Bachelor in Management of Information and Digital Contents (Plan: 376 - Estudio: 340)


Coordinating teacher: CARBO RUBIERA, JAVIER IGNACIO

Department assigned to the subject: Computer Science and Engineering Department

Type: Electives
ECTS Credits: 6.0 ECTS

Course: 4º
Semester:



Requirements (Subjects that are assumed to be known)
Programming (Python)
Objectives
- Analysis and synthesis skills - Planning and organization skills - Problem solving skills - Team work skills - Capacity to apply theoretical concepts - Critical Reasoning skills - Cognitive (acquired 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 (know how) 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.
Skills and learning outcomes
Link to document

Description of contents: programme
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 and methodology
Practical activities will include Python programming and the use of a public dataset.
Assessment System
  • % end-of-term-examination 40
  • % of continuous assessment (assigments, laboratory, practicals...) 60
Calendar of Continuous assessment
Additional Bibliography
  • Sebastian Raschka, Vahid Mirjalili . Python Machine Learning. Packt Publishing. 2017

The course syllabus may change due academic events or other reasons.