Objectives and competencies

Master studies are intended to help students acquire advanced knowledge of a specialised or multidisciplinary nature, often geared towards an academic or professional specialisation, as well as promoting an introduction to research work. This MSc degree in Data Science is aimed to be within this latter scenario.

The objective of the MSc in Data Science is: To prepare students for innovation in the area of Data Science, in two ways: firstly, the creation of innovative techniques and methods within the research area of Data Science and, secondly, the application of these techniques and methods relative to social and business reality as well as creating processes and innovative computer solutions.

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

This general objective can be completed 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 programmes, which are able to combine the specialised nature of the degree with creativity that underlies original and productive research directions. The second one is about the ability to be creative when addressing and solving problems through research.

Therefore, the global objective is materialised in more specific objectives that are the following:

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

Objective 2: To acquire skills in the usage of Data Science main arquitectures and technical tools.

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

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

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

Objective 6: To acquire advanced training and specialised and multidisciplinar knowledge to address research issues in Data Science.


The mentioned objectives are designed to enable students to acquire, during their studies, a set of general and specific competencies.

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

  • The general competencies are included in the first category. These are common to any Master degree 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 required competencies for a degree to be accredited as an MSc in Computer Science.
  • In the second category of competencies are those concerning the research orientation of the degree proposed or shared by any research-oriented Master offered by the School of Computer Science, and that are different from those shared by the professionally-oriented Masters.
  • And finally, in the third category will be the specific competences in Data Science that differentiate the proposed Master degree from other research Masters in the School of Computer Science.

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

According to the above, the graduate of the degree will be in a position to either join the labour force as a specialist in Data Science, or to continue their academic training and study for a PhD in the subject. Accordingly, the graduate will acquire an advanced knowledge of a specialised nature in Data Science. This allows the graduate to perform, as a professional, specific problem solving tasks incorporating these techniques and methods, which constitute recent results of research in the area. At the same time, due to the state-of-the-art nature of the acquired knowledge, and also due to the acquired ability to innovate, the graduate will be in a position to get started in research and consider enrolling in PhD studies.