Competencies and objectives

Provisional information. Pending approval by the School/Faculty Board.

 

Course context for academic year 2025-26

This is a core course in the first semester of the Master's Degree in Economics with Data Science. It provides students with practical and conceptual tools for managing and analyzing economic and business data. The course introduces relational and non-relational databases, methods for data extraction and processing, data visualization, exploratory analysis, and basic principles of data modeling in Economics.

 

 

Course competencies (verified by ANECA in official undergraduate and Master’s degrees) for academic year 2025-26

Skills/Skills

  • RA03 : Critically analyze research articles in Economics, identifying their essential contributions and weaknesses
  • RA11 : Use techniques and tools for selecting and extracting economic data.
  • RA12 : Use data visualization, data mining, and text mining techniques.
  • RA13 : Know how to apply data science techniques to real economic problems, both for research and decision-making

 

Conocimientos/Contenidos

  • RA10 : Be able to manage information and resources in the field of data science applied to economics, as well as master the use of specific software for this discipline

 

Skills/Competences

  • RA04 : Formulate relevant economic problems precisely and provide appropriate solutions using theoretical, empirical, or simulation-based analysis
  • RA06 : Master effective communication of research findings, using clear and precise approaches to convey complex information in an accessible and comprehensible way
  • RA14 : Be able to develop and learn autonomously about topics related to Economics and Data Science

 

 

 

Learning outcomes (Training objectives)

No data

 

 

Specific objectives stated by the academic staff for academic year 2025-26

By the end of the course, students will be able to:

1. Work with relational (SQL) and non-relational (NoSQL) databases, and connect heterogeneous data sources.

2. Collect, clean, process, integrate, and analyze large volumes of economic and business data.

3. Apply computational, statistical and visualization tools to solve applied economic problems.

4. Communicate insights effectively using appropriate visualization and reporting techniques.

 

 

 

General

Code: 49164
Lecturer responsible:
Albarrán Pérez, Pedro
Credits ECTS: 4,00
Theoretical credits: 0,00
Practical credits: 1,60
Distance-base hours: 2,40

Departments involved

  • Dept: FOUNDATIONS OF ECONOMIC ANALYSIS
    Area: FOUNDATIONS OF ECONOMIC ANALYSIS
    Theoretical credits: 0
    Practical credits: 0,8
    This Dept. is responsible for the course.
    This Dept. is responsible for the final mark record.
  • Dept: LANGUAGES AND COMPUTING SYSTEMS
    Area: LANGUAGES AND COMPUTING SYSTEMS
    Theoretical credits: 0
    Practical credits: 0,8

Study programmes where this course is taught