Publication in the Diário da República: Despacho n.º 11262/2016 - 19/09/2016
8 ECTS; 1º Ano, Anual, 20,0 T + 12,0 PL + 20,0 TP + 4,0 S + 32,0 OT + 10,0 O , Cód. 39323.
Lecturer
- Vasco Renato Marques Gestosa da Silva (2)
- Célio Gonçalo Cardoso Marques (2)
- Ricardo Nuno Taborda Campos (1)(2)
(1) Docente Responsável
(2) Docente que lecciona
Prerequisites
Not applicable
Objectives
The student should be able to understand, apply and use text mining, information extraction, processing and analysis tools using the Python programming language. Understand, design and apply cloud computing solutions and know how to use BI tools on the web.
Program
1.Introduction to Data Science
2. Data Science Python
3. Text Mining
4. Cloud Computing
5. Web Analytics
6. Business Intelligence in social networks
7. Competitive Intelligence
8. Business Intelligence (BI): Concepts
9. Phases of a BI process
10. SAP Business Objects/BI
11. BI solutions
12. Data modelling
13. Creation of reports and dashboards
Evaluation Methodology
Midterm assessment: Project I (5%) + Project II (15%) + Project III (20%) + Project IV (30%) +Test (30%)
Completion of all elements of assessment with a minimum mark of 7 (each)
Exam assessment: Exam (100%)
Bibliography
- Beasley, M. (2013). Practical Web Analytics for User Experience: How Analytics Can Help You Understand Your Users. Waltham: Morgan Kaufmann
- Burke, C. (2014). Competitive Intelligence the Internet Way. s.l.: SB2 Group
- Mahmood, Z. e Puttini, R. e Erl , T. (2013). Cloud Computing: Concepts, Technology & Architecture. s.l.: Prentice Hall
- Provost , F. e Fawcett, T. (2013). Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking. USA: O'Reilly Media
Teaching Method
Lecture and demonstration method. Analysis and resolution of practical cases.
Software used in class
