PROJECT DESCRIPTION

As part of the European Statistical Training Programme – Phase IV (ESTP IV), extensive efforts were made to develop, organize, and deliver training courses that equip statisticians within the European Statistical System (ESS) with cutting-edge methodologies and tools. A strong emphasis was placed on integrating new technologies such as Artificial Intelligence (AI), R, Julia, Python, and Machine Statistical Learning (MSL) into statistical production. The training covered a range of advanced topics, including statistical programming, data imputation, GIS scripting, Earth observation for statistics, and metadata exchange using SDMX. By collaborating with trainers from 14 EU National Statistical Institutes, the courses ensured a European dimension, facilitated the exchange of best practices, and strengthened methodological consistency across ESS members.

The project was designed to provide both theoretical knowledge and practical applications, enabling participants to effectively utilize modern tools in their statistical work. The inclusion of AI-driven approaches, machine learning techniques, and high-performance computing languages such as Julia helped enhance statistical modelling and forecasting capabilities. Hands-on workshops and interactive sessions encouraged skill development, while active participation in ESS meetings contributed to shaping best practices in official statistics. By fostering expertise in advanced methodologies and promoting interdisciplinary learning, the training played a crucial role in raising the overall quality and efficiency of European statistics.

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