Grado en Ciencia de Datos | Data Science

Program Overview

The Data Science program at Universidad Europea de Valencia equips students with the skills to analyze and extract value from large datasets. The curriculum, developed with industry experts, emphasizes foundational knowledge in mathematics, statistics, and programming, progressing to complex areas such as AI, machine learning, and big data. The program employs a project-based learning methodology, preparing graduates for diverse careers in technology, healthcare, and beyond. Graduates are highly sought after as data analysts, AI experts, and project managers in data science projects.

Program Outline

The curriculum has been developed by prominent industry experts, drawing on their experience from multinational companies like Amazon, Telefónica, Indra, and Unisys. The program emphasizes a progressive approach, starting with foundational knowledge in mathematics, statistics, and programming, and then progressing to more complex areas like artificial intelligence, machine learning, data mining, big data, and more. This comprehensive perspective provides students with a thorough understanding of the innovative professional world and highlights the importance of internationalization in their education, allowing them to choose various destinations in the US, Europe, and beyond. Graduates of the Data Science program will be capable of tackling diverse projects, ranging from predicting market trends in finance to developing algorithms for recognizing patterns in medical images. The demand for data scientists is booming as organizations recognize the strategic value of data for gaining competitive advantages.

Outline:

The program is structured over four years, with a total of 240 ECTS credits. The curriculum is divided into four semesters, with specific modules for each semester.

First Year:

• Análisis Matemático (Mathematical Analysis): 6 ECTS, Basic, Spanish
• Fundamentos de Estadística (Fundamentals of Statistics): 6 ECTS, Basic, Spanish
• Álgebra Lineal (Linear Algebra): 6 ECTS, Basic, Spanish
• Fundamentos de la Programación (Fundamentals of Programming): 6 ECTS, Basic, Spanish
• Programación Orientada a Objetos (Object-Oriented Programming): 6 ECTS, Basic, Spanish
• Introducción a la Ciencia de Datos (Introduction to Data Science): 6 ECTS, Compulsory, Spanish
• Organización y Gestión de Empresas (Organization and Business Management): 6 ECTS, Basic, Spanish
• Desarrollo e Impacto Personal (Personal Development and Impact): 6 ECTS, Compulsory, Spanish
• Liderazgo y Gestión de Equipos (Leadership and Team Management): 6 ECTS, Compulsory, Spanish
• Proyecto: Sistema de Información (Project: Information System): 6 ECTS, Basic, Spanish

Second Year:

• Matemáticas Discreta (Discrete Mathematics): 6 ECTS, Basic, Spanish
• Estadística Computacional (Computational Statistics): 6 ECTS, Compulsory, Spanish
• Análisis Explolatorio de Datos (Exploratory Data Analysis): 4.5 ECTS, Compulsory, Spanish
• Bases de Datos (Databases): 6 ECTS, Basic, Spanish
• Estructura de Datos y Algoritmos (Data Structures and Algorithms): 6 ECTS, Basic, Spanish
• Gestión de Proyectos en Ciencia de Datos (Data Science Project Management): 6 ECTS, Compulsory, Spanish
• Introducción en la Inteligencia Artificial (Introduction to Artificial Intelligence): 4.5 ECTS, Compulsory, Spanish
• Economía Digital (Digital Economy): 4.5 ECTS, Compulsory, Spanish
• Gestión de la Innovación (Innovation Management): 4.5 ECTS, Compulsory, Spanish
• Proyecto: Open Data II (Project: Open Data II): 6 ECTS, Compulsory, Spanish

Third Year:

• Modelos para la Toma de Decisiones/Models for Decision-Making: 9 ECTS, Compulsory, English
• Infraestructura y Computación en la Nube (Cloud Infrastructure and Computing): 6 ECTS, Compulsory, Spanish
• Fundamentos de Big Data (Fundamentals of Big Data): 6 ECTS, Compulsory, Spanish
• Aprendizaje Automático (Machine Learning): 9 ECTS, Compulsory, Spanish
• Visualización de Datos/Data Visualization: 6 ECTS, Compulsory, English
• Aplicaciones y Tendencias en Ciencia de Datos/Applications and Trends in Data Science: 6 ECTS, Compulsory, English
• Proyecto: Big Data II/Project: Big Data II: 9 ECTS, Compulsory, English

Fourth Year:

• Seguridad de Datos (Data Security): 4.5 ECTS, Compulsory, Spanish
• Legislación y Protección de Datos (Data Legislation and Protection): 4.5 ECTS, Compulsory, Spanish
• Creación y Gestión de Start-Ups (Start-Up Creation and Management): 4.5 ECTS, Compulsory, Spanish
• Responsabilidad Social y Ética (Social Responsibility and Ethics): 4.5 ECTS, Compulsory, Spanish
• Prácticas Académicas Externas (External Academic Practices): 18 ECTS, External Practices, Spanish
• Trabajo Fin de Grado (Final Degree Project): 12 ECTS, Final Degree Project, Spanish
• Análisis de Imágenes y Vídeos (Image and Video Analysis): 6 ECTS, Optional, Spanish

Teaching:

The program utilizes a Project-Based Learning methodology, allowing students to learn through real-world projects. The teaching faculty includes professionals with extensive experience in the field, including those from multinational corporations. The program also features regular seminars and workshops led by top professionals, providing students with training in the latest technologies and skills in management, leadership, and entrepreneurship.

Careers:

Graduates of the Data Science program are well-prepared for a variety of career paths in the technology sector and beyond. Some potential career paths include:

• Data Analyst
• Big Data Specialist
• Artificial Intelligence Expert
• Project Manager in Information Technology projects
• Freelance Consultant
• Start-Up Entrepreneur
• Researcher
• Teacher
These professionals can work in various organizations and sectors, including:
• Technology companies
• Public institutions
• Healthcare
• Environment
• Public safety

Other:

The program offers a variety of opportunities for students to gain practical experience, including:

• Real-world projects: Students participate in real-world projects from the first year, working with leading companies.
• Training sessions: Regular seminars and workshops led by top professionals provide training in the latest technologies and skills in management, leadership, and entrepreneurship.
• Internships: Students can participate in both curricular and extracurricular internships, gaining valuable experience in the field.
• Double degree options: Students can choose to pursue a double degree, combining the Data Science program with other programs like Physics, enhancing their career prospects.
The program is designed to provide students with a comprehensive and innovative education, preparing them for successful careers in the rapidly evolving field of data science.