Given the growing evolution and application of Artificial Intelligence techniques in various contexts, it is pertinent to develop skills that make it possible to understand, with an ethical sense, how these techniques can be used to benefit society.
This training aims to intersect the field of Social Sciences with the field of Data Science, with a view to developing skills in the extraction of knowledge from data that, in turn, promote improved productivity in industrial, social and technological organizations. In particular, mastering these skills enables professionals working in the context of Social Sciences to make data-driven decisions, rather than supporting decision-making processes through experience and instinct.
Objectives
- To provide students with a general but detailed notion of the main techniques for extracting knowledge from data;
- Acquire descriptive, predictive and prescriptive techniques;
- Focus on decision support systems in the context of the Social Sciences;
- Acquire the technical knowledge necessary to understand, model and implement decision support systems;
- Solving critical problems based on the technical skills acquired;
- Practical implementation of the techniques learned using appropriate software.
Target audience
Professionals in the Social Sciences (e.g. Psychology, Sociology, Communication, Management, Economics, Political Science) who wish to take advantage of (descriptive/predictive/prescriptive) data analysis and knowledge extraction approaches to optimize their decision-making processes in generalized organizational contexts.
Admission requirements
Hold a bachelor's or master's degree in teaching;
Selection and ranking criteria
Candidates will be selected and ranked according to the following criteria:
- Non-STEAM higher education;
- Academic curriculum, taking into account the classification of academic degrees obtained (tie-breaking criterion).
The final ranking of candidates will be expressed on a scale of 0 to 20 points.
Evaluation
Trainees will be assessed on a scale of 0 to 20 points in each of the modules that make up the training, using the assessment tools that will be defined by the teacher. These assessment instruments must be consistent with the objectives and teaching methodologies to be developed in this training, and this consistency must be duly explained in the characterization sheets of the various curricular units.
Investment
- Application|50€
- Registration|0€
- Current UCP students 50% discount on application and tuition fee
- Former UCP students 10% discount on application
- Tuition fee €110 (equal to the value of the scholarship)
- UCP employees and professors exempt from tuition and application fees
