Harnessing climate data: Classification and predictive analytics for tourism

In this workshop, we will introduce key theoretical concepts in data classification and predictive analytics. Participants will learn how to use historical data to classify and predict future outcomes, a fundamental skill in data science. These concepts will be illustrated through a practical use case involving the Tourism Climate Index (TCI), using tools currently offered by BDTI.

All the tools used during these workshops are available for free to EU public administrations through the BDTI platform. Learn how to apply for BDTI here.

The use case will involve predicting TCI classifications based on historical weather data, demonstrating the application of machine learning techniques to categorise data effectively. This approach not only aids tourists in making informed travel decisions based on climatic conditions but also serves as a practical example of data classification techniques.

What you’ll get from this workshop:

• A foundational understanding of data classification and predictive analytics
• Learn to use Jupyter Notebooks for data processing and MinIO to store and manage the data securely.
• Hands-on experience in applying machine learning models to real-world data
• Skills in data preprocessing, feature engineering, and model evaluation.
• Insights into the use of data-driven recommendations in various sectors, such as tourism
• Resources and tools to further develop expertise in data science and analytics

Who should join?

This workshop is ideal for data professionals, public administrators, and anyone interested in learning about data classification and predictive analytics. It is particularly suited for beginners, offering a comprehensive introduction to these concepts without requiring prior experience. This course is perfect for those looking to apply data-driven approaches to enhance decision-making in sectors like tourism and beyond.

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