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Micro-accreditation in Data Science for Hospitality & Tourism

Data Science Topo

Micro-accreditation in Data science for Hospitality & Tourism I (Descriptive Analytics)

Micro-accreditation in Data science for Hospitality & Tourism I (Descriptive Analytics) aims at introducing the basic concepts of data exploration and knowledge mining to support advanced data analytics and decisionmaking. During the semester, students will be introduced to Python and Jupyter Notebook as a working environment. We will explore techniques to assess the quality of data, 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 develop a data-driven descriptive analysis independently to extract useful and relevant knowledge to support business decisions.

Who is it for?

This course is intended for professionals in the field of tourism and hospitality who want to understand a set of concepts and methodologies that can be used for effective and successful management of digital transformation projects.

Learning outcomes:

By the end of the course, the students will be able to:

  • Explain the role of data science in current business activities and how it can be used to derive knowledge on specific problems and support decision-making.
  • Prepare data for analysis and Identify adequate data mining techniques.
  • Explore a dataset and Extract knowledge using simple statistics and correlation analysis.
  • Understand the difference between supervised and unsupervised learning.
  • Explain the difference between forecasting, classification, and clustering problems;
  • Identify the most common metrics for distance and similarity.
  • Apply clustering analysis to Hospitality and Tourism problems.
  • Choose the adequate metrics to profile clustering results
  • Perform network analysis and Extract network measures to extend the depth of your models and data understanding.
  • Support your decisions using data-driven methods.

General Information

Course Delivery

Dates: The classes will start in September 2023, running after working hours (after 6:30 p.m.). 

Format: Hybrid (students may choose to attend in person or online via zoom). The exams will be on-site.

Entry Requirements:

To enter this program, applicants must meet the following requirements:

  • Hold a bachelor's degree in a compatible field (completed by September 2023);
  • Be proficient in English (spoken and written).

Registration: through the form until August 25th.

Registration payment: until August 29th.

Selection Process: The selection process is based on the analysis of academic and professional curriculum. The members of the Admissions's Jury Panel may decide to hold an interview with all or some candidates - face-to-face or videoconference.

Tuition Fee:

The tuition fee is €1.450. However, the 2023-24 edition, starting in September 2023, has the special support of TIA | PRR, so there will be a discount of around 50% for residents in Portugal during the entire program, with the tuition fee for these Students being €725.

The program will only start after the enrollment of at least 15 Students and the special value of the TIA | PRR, cannot be combined with other discounts.

Duration and ECTS

This course has a duration of 28 hours and awards 7.5 ECTS to participants.


The course will be taught in English.

Professor Responsible

Flávio Pinheiro

Program Coordinator

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