Nuno António

Invited Assistant Professor

Nuno António holds a PhD degree in Computer Science by ISCTE-IUL, a Masters in Hotel Administration and Management by the School of Management, Hospitality and Tourism of the University of the Algarve, and a degree in Software Engineering by ISMAT.

His research interests are related to the application of Data Science, Machine Learning, Text Mining, Data Mining, and Big Data in hospitality and tourism, retail, health, and other domains.

His work has been published in major scientific journals and conferences, including International Journal of Contemporary Hospitality Management, Cornell Hospitality Quarterly, Journal of Travel Research, Information Technology & Tourism, Data Science Journal, IEEE ICMLA, among others.

He is actually Chief Technology Officer at Itbase/WareGuest, a company specialized in the development of software and decision support systems for the hospitality and retail industries. Additionally, he is an invited assistant professor of Machine Learning, Big Data, Data Mining and Social Media Analytics courses in Nova IMS.

Nuno is certified in Business Intelligence, specialization of Business Analytics by TDWI – The Data-Warehousing Institute. He is certified as ScrumMaster and member of the Scrum Alliance and, he is also certified as Project Management Associate by IPMA - International Project Management Association.

Courses By Speaker

Critical Thinking and Data-Driven Decision Making

Critical thinking (the analysis of available facts, evidence, observations, and arguments to form a judgement) and data-driven decision making (the process of using data to inform decision-making processes and validate a course of action before committing to it) are complex subjects which include the rational, skeptical, and unbiased analysis or evaluation of factual evidence.  However, both of these topics have always been at the forefront of the required success skills in the future.  This program will provide the learners with a deeper understanding of critical thinking, help them recognize cognitive biases and barriers to critical thinking and provide them the skills to develop approaches to critical thinking.  It will also provide the guidelines on how to implement structured decision-making processes and start their journey towards building a data-driven organization and culture.

Course Outline:

  • What is critical thinking
  • The five pillars of critical thinking
  • Cognitive biases and barriers to critical thinking
  • Critical thinking approaches
  • Implementing structured decision-making processes
  • Key terms, frameworks, and the data-driven decision-making process
  • Data ethics and privacy
  • Building a data-driven organization and culture
  • Data characteristics and data mining process models
  • Technologies and tools employed in data-driven decision-making
  • Descriptive analytics and data visualization
  • Predictive and prescriptive analytics
  • Data-driven decision-making application cases