IPLUSO 23554

Advanced Data Science

• ApresentaçãoPresentation

  The course aims to deepen knowledge and skills in the field of data analysis and interpretation, especially from organizational, social and digital contexts. Content related to database structuring and management is covered, as well as the application of advanced mixed analysis methods, with qualitative and quantitative data, and the effective communication of the results obtained.  It is intended that students develop the ability to design, implement, and evaluate analytical processes aimed at solving complex problems and supporting decision-making, promoting a critical, ethical and reasoned approach to the use of data.
• ProgramaProgramme

  Introduction to applied data science; Ethics, privacy, and data protection (GDPR) in information collection and processing; The role of data in problem solving; Quantitative data collection through questionnaires: types of questions, response scales, common errors in question formulation, pilot testing, and instrument validation. Methods of qualitative analysis of online and offline data: coding, categorisation, identification of patterns and themes in language; Computer support for analysis using specialised software for organising and exploring data; Integration of qualitative and quantitative data for comprehensive results; Exploratory analysis of mixed data; Interpretation and communication of analytical results; Application of the methods studied to case studies in digital environments.
• ObjectivosObjectives

  Knowledge: Students are expected to acquire knowledge of the fundamental principles of data science, particularly with regard to ethical processes, data collection, organisation, analysis and interpretation from different contexts, with a view to problem solving. Skills: Students should develop skills to structure data sets, select appropriate methods of analysis, interpret results and communicate conclusions in a clear and reasoned manner, using analytical approaches appropriate to the context of the problem under study. Competencies: At the end of the course, students should be able to apply methodologies (individually or in combination) to solve specific problems, support decision-making processes based on empirical evidence, and act critically and responsibly in the use of data, respecting ethical and legal principles.
• BibliografiaBibliography

  Andreotta, M., Nugroho, R., Hurlstone, M. J., Boschetti, F., Farrell, S., Walker, I., & Paris, C. (2019). Analyzing social media data: A mixed-methods framework combining computational and qualitative text analysis. Behavior research methods, 51(4), 1766-1781. https://doi.org/10.3758/s13428-019-01202-8 Morettin, P. A., & Singer, J. M. (2020). Introdução à Ciência de Dados. Fundamentos e Aplicações. https://www.ime.usp.br/~jmsinger/MAE0217/cdados2020jun03.pdf Vasconcelos, J. B., & Barão, A. (2017). Ciência dos dados nas organizações. http://hdl.handle.net/10884/1424
• MetodologiaMethodology

  The course will be developed through theoretical and practical classes, combining the presentation of fundamental concepts with the resolution of applied exercises and the analysis of case studies, from the perspective of Service Learning (SL) in the academic community. Active learning methodologies will be promoted, encouraging student participation in the exploration of data sets, discussion of results, and critical reflection on the analytical processes used.
• LínguaLanguage

  Português
• TipoType

  Semestral
• ECTS

  5
• NaturezaNature

  Mandatory
• EstágioInternship

  Não