Bachelor’s Degree in Data Science

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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.

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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.
• Have a B2 level (or equivalent) in English.

CAREER OPPORTUNITIES

The programme trains graduates to work as data analysts in any sector related to information analysis and the production of results for decision-making.

More specifically, it must enable them to carry out tasks in companies and organisations such as data analysis and the provision of reports to evaluate business processes; the analysis and monitoring of key indicators; advising on the use of big data; and the construction of models and proposals for the application of machine learning, among others. This is stipulated in Article 3 of Decree 81/2021 of 10 March 2021, which created the state bachelor’s degree in data science.

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 (5 ECTS)

○ Statistical Computing II (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)

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