Ciência de Dados em Hotelaria e Turismo I

Objetivos

The Data Science for Hospitality and Tourism I (Descriptive Analytics) curricular unit introduces the basic concepts of data exploration and knowledge mining to support advanced data analytics and decision-making. During the semester, students will be introduced to Python and Jupyter Notebook as a working environment. We will explore techniques to assess data quality, prepare data for analysis, characterize, and describe a dataset, use clustering techniques, and network analysis for client/product segmentation. By the end of the semester, students will be equipped with the skills and toolset to independently develop a data-driven descriptive analysis to extract practical and relevant knowledge to support business decisions.

 

Practical activities will be developed in Python programming language. We will use the popular and valuable libraries available (Pandas, Numpy, Scipy, Scikit Learn, Matplotlib, Seaborn, and stats model) that Python, the favorite framework among data scientists.The curricular unit has a strong active learning component. Hence, we expect students to participate in class activities and read the recommended weekly materials beforehand.

Caracterização geral

Código

400112

Créditos

7.5

Professor responsável

Vitor Manuel Cruz Manita

Horas

Semanais - A disponibilizar brevemente

Totais - A disponibilizar brevemente

Idioma de ensino

Português. No caso de existirem alunos de Erasmus, as aulas serão leccionadas em Inglês

Pré-requisitos

A disponibilizar brevemente

Bibliografia

Método de ensino

Método de avaliação

Conteúdo