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An Introduction to Artificial Intelligence in the Tourism Industry

Published: 26 April 2021

Discover how artificial intelligence is set to shape the future of tourism, in this introductory tourism management course.

Artificial Intelligence is the ability of computer programs and robots to mimic human natural intelligence. AI in the hospitality industry often focuses on customer service and commitment. It can be about various online tools that make it easy for you to book a trip, a restaurant visit or translate into different languages. It is common for hotels or service companies to use, for example, chatbots, a digital person, to be able to quickly answer customers' questions. By automating and streamlining a company's processes, both time and money can be saved.

About the course:

You will learn the basic concepts and terms in AI, such as machine learning and neural networks. You also get to reflect on questions about AI ethics.

VR and AR are getting more and more attention and are being integrated into different industries. In the course, you explore the basics of computer graphics applications in VR / AR, VR / AR frameworks and their integration with the hospitality industry.

Who is the course for?

The course is for you who want to expand your knowledge in AI, and then especially connected to the hospitality industry - regardless of whether you are an owner, employee, entrepreneur or senior executive.

What are you learning?

  • Understand what AI is and how it changes our lives.
  • Discover the possibilities of using AI in the hospitality industry.
  • Describe and reflect on ethical issues around AI.
  • Explore basic machine learning methods, such as neural networks, cluster methods, and classification methods.
  • Demonstrate a basic understanding and knowledge of the components of AI such as identified theories of machine learning.

Teacher in charge

Marcus Liwicki

Marcus Liwicki, Professor and Head of Subject, Deputy Vice-Chancellor for applied AI

Phone: +46 (0)920 491006
Organisation: Machine Learning, Embedded Intelligent Systems LAB, Department of Computer Science, Electrical and Space Engineering