Data Science for Hospitality and Tourism I

Objectives

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.