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Mestrado em Engenharia Informática-Internet das Coisas

Big Data Processing

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Publication in the Diário da República: Despacho n.º 13495/2022 - 18/11/2022

10 ECTS; 1º Ano, 1º Semestre, 30,0 PL + 30,0 TP + 30,0 OT

- Ricardo Nuno Taborda Campos


1. Understand the importance of Python in Data Science
2. Be aware of ethical issues in the process of collectinf and use of information
3. Master the data collection process
4. Knowing how to apply information extraction methods
5. Be familiar with the 5V's
6. Knowing how to use the main frame

1. Python in the context of Big Data
2. Data Ethics and Privacy
3. Data Acquisition
4. Information Extraction
5. Introduction to Big Data (Map-Reduce Programming Model)
6. Big Data Frameworks

Evaluation Methodology
Periodic evaluation: Project (60%) + Exam (40%)

The delivery of the project is mandatory for obtaining approval in the course during the periodic evaluation which assumes a minimum of 70% attendance. The delivery after the foreseen period implies the reproval of the student, making it impossible for him/her to propose to the exam. Students are also automatically excluded from the exam if they obtain a score of less than 6 values in the project or if they do not reach a minimum number of attendances.

Final Assessment: Exam (100%)

- Santos, M. e Costa, C. (2019). Big Data - Concepts, Warehousing, and Analytics. (pp. 1-312). Lisboa: FCA
- Foster, I. e Ghani, R. e Jarmin, R. e Kreuter, F. e Lane, J. (2017). Big Data and Social Science. A Practical Guide for Methods and Tools. (pp. 1-349). New York: Taylor & Francis
- Erl, T. e Khattak, W. e Buhler, P. (2016). Big Data Fundamentals: Concepts, Drivers & Techniques. USA: Prentice Hall
- Sarkar, D. (2021). Text Analytics with Python: A Practitioner's Guide to Natural Language Processing. (pp. 1-661). USA: Apress

Teaching Method
Exposure of the syllabus using the expository and demonstrative method. Analysis and resolution of practical cases through Python notebooks. The acquired knowledge will be evaluated through the realization and presentation of projects

Software used in class




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