Bachelor’s Degree in Data Science

ES CAT EN

Request
Information

Online 3 years (180 credits)

The Bachelor’s Degree in Data Science prepares university undergraduates to address complex problems that involve data sets of diverse typology, apply their scientific-technical knowledge to develop innovative solutions, and work in multidisciplinary teams. In addition, you will acquire critical capacity in the analysis and interpretation of results, and you will be able to communicate easily in different contexts.

I WANT TO ENROLL

OBJECTIVES

The Bachelor’s Degree in Data Science prepares university undergraduates to address complex problems that involve data sets of diverse typology, apply their scientific-technical knowledge to develop innovative solutions, and work in multidisciplinary teams. In addition, you will acquire critical capacity in the analysis and interpretation of results, and you will be able to communicate easily in different contexts.

REQUIREMENTS

• High School Diploma
• University entrance exam for those over 25
• Advanced Diploma in Administration or similar.

CAREER OPPORTUNITIES

The professional opportunities cover very diverse areas, since data science is a transversal discipline that is applied in sectors as varied as health, finance, marketing, logistics, public administration, the environment, education or industry. This allows – both new graduates and professionals seeking reorientation – access to responsibility roles related to the processing and strategic use of data within organizations in any field.

Study plan

YEAR 1

Semester 1

○ Fundamentals of Programming (Python and R) (5 ECTS)

○ Practical Projects and Advanced Programming Techniques (5 ECTS)

○ Linear Algebra (5 ECTS)

○ Linear Algebra and Calculus for Data Science (5 ECTS)

○ Statistics and Probability (10 ECTS)

Semester 2

○ Digital Tools and Collaborative Work in Data Science (10 ECTS)

○ Information Systems and Relational Databases (5 ECTS)

○ NoSQL Databases and Integration with Python/R (5 ECTS)

○ Introduction to Data Science and Data Ethics (10 ECTS)

YEAR 2

Semester 1

○ Multivariate Analysis (10 ECTS)

○ Statistical Computing I: Inference and Simulation (5 ECTS)

○ Statistical Computing II: Advanced Computational Models and Methods (5 ECTS)

○ Data Visualization and Storytelling (10 ECTS)

Semester 2

○ Data Mining (10 ECTS)

○ Fundamentals of Machine Learning (5 ECTS)

○ Advanced Machine Learning and Applications (5 ECTS)

○ Data Architecture (5 ECTS)

○ Big Data and Distributed Systems (5 ECTS)

YEAR 3

Semester 1

○ Introduction to Research and Scientific Methodologies (12 ECTS)

○ Elective Course 1 (6 ECTS)

○ Elective Course 2 (6 ECTS)

○ Elective Course 3 (6 ECTS)

Semester 2

○ Internships (15 ECTS)

○ Bachelor Final Project (15 ECTS)

PRIVACY POLICY COOKIE POLICY LEGAL NOTICE QUALITY POLICY

CREDIT TRANSFER REGULATIONS