From 15 to 19 December 2025, capacity-building trainings on Data Analysis and Applied AI were organized by Farmahem as a Regional Executive Agency in Skopje, North Macedonia, in the frame of the SDC’s Landscape Fire Management in the Western Balkans (LFMWB) Programme. The training brought together representatives from Regional Executive Agency, Country Project Staff and Regional Fire Monitoring Center. The training was hosted at Farmahem and designed to strengthen analytical, digital, and AI-driven capacities essential for landscape fire management (LFM).
The training combined data analysis skills with applied AI tools, responding directly to the growing need for evidence-based decision-making, improved monitoring, and efficient reporting related to LFM.
The first part of the training, Data Analysis and Visualization (16–17 December), was led by Nenad Ristov and focused on building practical skills for working with environmental datasets. Participants explored how structured data analysis supports monitoring, reporting, and strategic decision-making in landscape fire management contexts.
Through hands-on sessions, participants learned how to prepare and clean datasets in Excel, analyze data using Pivot Tables and AI-assisted tools such as Copilot, and translate results into clear visualizations and data stories. The training also introduced Power BI, guiding participants through data transformation in Power Query, basic data modelling, and the design of interactive dashboards tailored to environmental and fire-related data.
By the end of this module, participants were able to move from raw data to structured insights, using modern tools to better understand trends, patterns, and spatial information relevant to their daily work.
The second part of the training, Applied AI and Automation (18 December), was delivered by Luka Anicin and focused on the practical use of artificial intelligence in data analysis, reporting, and workflow automation.
Participants explored leading AI platforms such as ChatGPT, Microsoft Copilot, and Google Gemini, learning how to select the right tool for different tasks. Special attention was given to prompt engineering, data security principles, and responsible AI use.
The hands-on component demonstrated how AI can support real workflows, including EFFIS data processing, AI-assisted analysis and visualization, automated report writing, and presentation generation aligned with LFMWB reporting standards. The training concluded with an introduction to AI automation tools such as n8n, showcasing how data acquisition and reporting processes can be streamlined and scaled.
This training marked an important step in strengthening regional capacities for data-informed, AI-supported LFM. By combining applied AI and automation, participants gained practical skills that can be directly integrated into their workflows, contributing to more efficient reporting, improved coordination, and stronger evidence-based decision-making across the region.
The activity reflects the LFMWB Programme’s continued commitment to capacity building, innovation, and the practical application of digital tools in LFM.