Class Topics in Data Engineering for Data Science

This course focuses on "data engineering" and its intersection with "data science". In this context, it is intended that students gain technical skills in several independent but related topics. The most relevant areas of this course are databases and programming, which are the fundamental skills one needs to be able to play the role of "data engineer" in academic and/or industrial projects. The inclusion of the course in the masters program is justified with the importance of data collection, validation and processing skills in order to be able to have data that can be "explored" with the knowledge acquired in the other curricular units.

Not applicable

Introduction to Data Engineering Git & GitHub Introduction to version control systems Learning elementary work processes using the Git software and the GitHub online platform Databases & SQL Relational Databases SQL language SQL Injection (elementary notions) Python Programming From the data extraction and data processing points of view From the exploratory data analysis point of view Algoritmic complexity and efficiency It's importance when dealing with large amounts of data Jupiter notebook Linux Introduction to the GNU/Linux operating system File system navigation (commands)

Theoretical-practical classes with exposition of theory and presentation of practical examples. Exercises to be carried out during the class, with the support and validation of the Teacher. Exercises to do at home. Assessment: 3 mini-tests and a project

Damas, Luís - SQL - Structured Query Language. 14ª edição. Portugal. FCA, 2017. ISBN: 9789727228294