AppliediT was in I Data Science Master, Seville

The main reason Data Science (DS) has become an indispensable professional area within any company, institution or organization of an organization is in the interest – in many cases the need – to take advantage of the available data or accessible to the organization. Exploitation of such data becomes essential to extract actionable knowledge, ie, useful for analyzing, diagnosing, predicting, etc. in fields of scientific, economic, health interest and practically in any socio-economic field. To this reason, it is joined by the provision of powerful technologies for data processing.

The professional profile of DS is private. The data analysis team of an organization must coexist with computer scientists who maintain and manage the databases with scientists who apply and adapt algorithms of automatic learning to the specific environment under study to apply them successfully to the available data. It is this scientific profile that aims the Master in Data Science and Big Data offered at the Permanent Training Center: the updating of knowledge of professionals working with data and technical specialization in DS for professionals in Statistics, Mathematics or Computing.

Structured in an academic course, it begins with two modules of leveling of knowledge in programming, automatic learning and statistical principles. The following are modules oriented to all the fundamental facets of the activity of a data scientist such as the management of databases and focusing on Artificial Intelligence and Statistics applied to data from various approaches (metaheuristics, spatio-temporal models , etc.). The module of Natural Language Processing and Collective Intelligence present applications and computational models for the treatment of human-generated information. They also focus on professional issues of the scientific profile of data such as visualization of information and data and questions about the management of data analysis projects. The final Master’s Work will focus on solving real data problems using the techniques worked during the course. Collaboration agreements are currently being finalized with companies interested in the profile of graduates to support the Master’s activities and to train their employees.

The teaching activities are done in laboratories of the Resource Center for Learning and Research Antonio Ulloa of the US. The faculty is made up of professors from the Departments of Statistics and Operational Research and from CC Computación and IA of the US, along with data professionals from companies, specialists of recognized prestige in some aspects of DS and professors from other universities.

 

 

Goals

  • To enable the student in the necessary competences for the computational and statistical treatment of data, using computer techniques and Artificial Intelligence.
  • To train graduates in scientific data analysis.
  • Implement graduate studies that train the graduate as a data scientist within the company.
  • Facilitate applied training in Data Science for graduates.
  • To train graduates in the scientific management of solutions for Big Data.
  • To provide the entrepreneurs and institutions of the region with qualified specialists in the exploitation of data and extraction of knowledge of them.
  • To update the skills and knowledge of professionals in Statistics or Computing working in the public or private sector.

 

Competitions

  • Ability to apply the acquired knowledge and to solve problems in new or little known environments within broader and multidisciplinary contexts, being able to integrate this knowledge.
  • Ability to integrate knowledge and face the complexity of making judgments based on information that, incomplete or limited, includes reflections on social and ethical responsibilities linked to the application of their knowledge and judgments.
  • Ability to communicate their conclusions and the latest knowledge and reasons that support them to specialized and non-specialized audiences in a clear and unambiguous way.
  • That students have the learning skills that allow them to continue studying in a way that will be largely self-directed or autonomous.
  • Students will be able to perform a critical analysis, evaluation and synthesis of new and complex ideas.
  • Students should be able to communicate with their colleagues, with the community with which they share professional interests as a whole and with society in general about their areas of knowledge.
  • Students will be able to foster, in academic and professional contexts, technological, social or cultural advancement within a knowledge-based society.
  • Students will be able to analyze texts from the area in other relevant languages ​​in the scientific field.
  • Students will be able to assess the quality of new methods of knowledge creation and management.
  • Ability to formulate global and reasoned opinions on projects of creative-technological scope.

 

Evaluation procedures

  • Assistance
  • Jobs
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