CCBRE Scientific Seminar: Practical AI for Real-World Problem Solving

The "Academy for Sustainable Innovation and Scientific Research" Foundation supported the organization and hosting of the CCBRE scientific seminar titled "Practical Artificial Intelligence for Solving Real-World Problems." The seminar is a direct example of the Foundation’s mission—to bridge the gap between science and practice and to build professional skills that bring real value to industry, the environment, and society.

Artificial intelligence and machine learning are no longer abstract research topics—they are powerful tools for tackling real and complex challenges. The workshop was created precisely to bridge the gap between theoretical AI concepts and practical, applicable solutions.

The course “Practical AI for Solving Real-World Problems” introduces participants to the full machine learning workflow using Python, with a strong emphasis on hands-on work, real-world datasets, and model interpretability. Rather than limiting itself to mathematical formalism, it demonstrates how AI systems are designed, trained, evaluated, and used in practice—from raw data to actionable insights.

Participants work with data from the fields of the environment, biomass, waste management, and remote sensing—data that reflect the real-world challenges addressed by the Center for Clean Technologies and Efficient Use of Biomass (CCBRE). Key topics include data preprocessing, feature extraction, supervised learning (classification and regression), unsupervised learning (clustering and principal component analysis), model evaluation, and the responsible use of AI results in decision-making.

By the end of the course, participants will be able to:

• understand how AI models are trained on data;
• design reliable and practically applicable machine learning workflows;
• critically evaluate and interpret model results;
• apply AI methods to real-world problems in the fields of sustainable development and industry.

The workshop is suitable for engineers, researchers, decision-makers, and professionals who want to go beyond buzzwords and acquire practical, transferable skills in artificial intelligence with direct real-world applications.