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Course: 2022/2023

Big Data

(17484)

Study: Bachelor in Management of Information and Digital Contents (340)

Coordinating teacher: CARBO RUBIERA, JAVIER IGNACIO

Department assigned to the subject: Department of Computer Science and Engineering

Type: Electives

ECTS Credits: 6.0 ECTS

Course: 4º

Semester:

Requirements (Subjects that are assumed to be known)

None

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 Architecture 3.- Big Data Techniques 4.- Information Systems and Big Data 5.- Machine Learning and Big Data

Learning activities and methodology

Practical activities will include Python programming and the use of a public dataset.

Assessment System

The final exam will evaluate the theoretical contents of the subject, with a weight of 50%.
The practical works carried out along the semester are weighted with the other 50%.

% end-of-term-examination 50
% of continuous assessment (assigments, laboratory, practicals...) 50

Additional Bibliography

Sebastian Raschka, Vahid Mirjalili . Python Machine Learning. Packt Publishing. 2017

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