Spain

This course covers the concept and areas of education, the dimensions, contexts, and agents of education, and the purposes and values of education in today's world. 

This course discusses Decision Analysis (DA), the discipline comprising the philosophy, theory, methodology, and professional practice necessary to address important decisions in a formal manner. It explores procedures, methods, and tools for identifying, representing, and formally assessing important aspects of a decision, as well as translating the formal representation of a decision and its corresponding recommendation into insight for the decision-maker and other stakeholders. 

This course offers 40 hours of intermediate study of Spanish language for students at a B1.1 to B2.2 level, according to the Common European Framework of Reference for Languages.

This course offers a study of data integration and visualization. Topics include: data integration models; data acquisition; noSQL databases in data integration; situational awareness and interpretation in the Big Data era; visual analytics; principles of human-machine interaction; visual interfaces; temporal and geo-spatial data processing; applications of visual analytics.

The course offers a study of the concept and method of psychobiology, evolution, development and inheritance, comparative and evolutionary psychology, and principles of cell signaling and transmission in the nervous system. 

This course offers a study of the foundations of the psychological assessment process including history, concepts, and general methodology. It covers psychological reports and psychopathological and personality assessment tests.

This course offers an advanced study of the natural, exploring various concepts of graphical representation of the model, such as chiaroscuro and line, among others. Topics include: artistic strategies based on body fragmentation; portrait issues; attitude and pose; the imaginary and the represented; body metaphors; the idea of reality; processes in drawing.

This course offers an introduction to data science for genomic data. It discusses basic algorithms for genome sequencing, compares DNA sequences or proteins, and analyzes databases with the genomic profiles of different patients for the extraction of information. Other topics include: computational methods for analyzing and performing DNA data sequencing; advanced statistical methods for the analysis of genomic data; statistical tests for the extraction of conclusions.