Details

Category: Discipline

• Cady, F. (2017). The Data Science Handbook. Wiley. Reis, F.L. (2018) Investigação Científica e Trabalhos Académicos: Guia Prático. Lisboa: Edições Sílabo.
• Data Science
• 6321
• 5140
• Final Course Work
• ISMAT6321-5140
• 3
• 14
• 0
• 12
• Não
• Português
• The teaching methodology includes tutorial and theoretical-practical teaching by the advisor. The development of the project in a public or private organization is privileged. In that case, a co-supervisor should be appointed in the organization. The methodologies are adapted to the specificities and needs of each project.  
• Mandatory
• It is intended with this UC that students develop a complete project of Data Science, with real data, primary or secondary.  LO1: Understand the context of the problem, define the objectives, the public of interest, the appropriate data and analysis techniques and the project's contribution to management, science or society; LO2: Develop the state of the art on the subject and the techniques to be applied; LO3: Defining and adopting the necessary ETL (Extract, Transform, Load) procedures, taking into account the available data sources, the respective levels of structure and the possible presence of missing and / or outliers, in order to ensure quality of the data; LO4: Dealing with data access and privacy problems; LO5: Apply the appropriate data analysis techniques to answer the project's objectives, using the appropriate computational resources; LO6: Prepare a scientific document suitable for the dissemination of the project; LO7: Make an oral presentation of the project results.  
• S1. Contextualization, justification, objectives and methodology of the Data Science project S2. State of the art elaboration S3. Data processing and analysis S4: Discussion of results and obtaining insights S5. Preparation of scientific document and oral presentation of the main results  

• A avaliação contínua terá duas componentes:

  - Documento escrito: 70%;

  - Apresentação oral: 30%.

  Dada a natureza da UC, não pode ser avaliada por exame.

   

   

   

• Semestral
• The Final Course Work curricular unit represents the culmination of the student's academic training, providing an opportunity to integrate and apply the knowledge, skills and methodologies acquired throughout the programme. Through the development of a project, applied study or research work, students demonstrate their ability to identify and solve problems independently, using scientific methods and Data Science techniques to address real-world challenges.