Objectives and competencies

Master’s studies are intended to help students acquire advanced knowledge of a specialized or multidisciplinary nature, often geared toward an academic or professional specialization, or to promote an introduction to research work. This MSc degree in Data Science aims to fall under the latter scenario.

The objective of the MSc in Data Science is: To prepare students for innovation in the field of Data Science in two different ways: firstly, through the creation of innovative techniques and methods within the research field of Data Science and, secondly, by applying these techniques and methods in relation to our social and business reality, as well as by creating processes and innovative computer solutions.

Consequently, a higher degree of knowledge in Data Science will be provided to Computer Engineering and Science and Technology professionals who study this course. This will enable them to deal with, and solve, problems of both a scientific and of a technological nature by using the techniques and methods from recent research.

This general objective can be reached by using two additional and intrinsic goals. Firstly, the idea of innovating in order to research and, simultaneously, the idea of researching in order to innovate. The first goal suggests innovative programs, which are able to combine the specialized nature of the degree with the creativity that underlies original and productive research directions. The second goal concerns the ability to be creative when addressing and solving problems through research.

As such, the global objective is materialized into more specific objectives, which are:

Objective 1: To develop the knowledge and skills to select the most suitable storage and management solution for both structured and non-structured data for a given problem. To develop knowledge of acquisition, extraction, manipulation and data-transformation processes in different environments.

Objective 2: To acquire skills in the use of Data Science’s main architectures and technical tools.

Objective 3: To develop knowledge of statistical techniques and machine learning methods to perform descriptive and predictive data analysis.

Objective 4: To provide students with the resources they need to be creative when addressing scientific and technological issues in Data Science.

Objective 5: To implement the knowledge they have learned to build a Data Science Project based on a real work environment.

Objective 6: To acquire advanced training and specialized and multi-disciplinary knowledge to address research issues in Data Science.


The aforementioned objectives are designed to enable students to acquire a set of general and specific competencies throughout the course of their studies.

The competencies of the MSc degree in Data Science are structured into three categories.

  • The general competencies are included in the first category. These are shared by all Master’s degrees in Spain (by Royal Decree), or are proposed by the Universidad Politécnica de Madrid, or are included in the standard EURO-INF, which defines the competencies required for a degree to be accredited as an MSc in Computer Science.
  • The second category includes competencies concerning the research orientation of the degree proposed or shared by all research-oriented Master’s degrees offered by the School of Computer Science, and which are different from those shared by the professionally-oriented Master’s degrees.
  • And finally, the third category includes the specific competencies in Data Science that set the proposed Master’s degree apart from other research Master’s degrees at the School of Computer Science.

This link shows these three sets of competencies which, as mentioned above, the students should have acquired after graduation.

As mentioned, degree graduates will be in a position to either join the workforce as a specialist in Data Science, or to continue their academic training and study for a PhD in the subject. Accordingly, graduates will acquire advanced specialized knowledge  in Data Science. This allows graduates to perform, as a professional, specific problem-solving tasks by incorporating these techniques and methods, which are the result of recent research results in the field. At the same time, due to the state-of-the-art nature of the acquired knowledge, and also due to the ability to innovate that graduates have learned, they will be in a position to commence researching and consider enrolling in PhD studies.