The aim of this course is to introduce students to the potential use of artificial intelligence and machine learning techniques in the field of food safety; to teach data-based solution approaches for early detection, control and prevention of food-borne risks. It is aimed that students will gain the competence to develop decision support systems in food safety processes by understanding the advantages and limitations of different algorithms.

This course examines the application of artificial intelligence (AI) and machine learning (ML) techniques in the field of food safety. Focus is on topics such as food-borne risk detection, traceability systems, quality control processes, and contaminant prediction. Students will learn how to select appropriate algorithms for food safety data analysis, apply basic modeling methods, and develop AI-powered decision systems. Innovative AI-based solutions for topics such as HACCP, food traceability, and contamination prevention will also be discussed. The course is supported by real-world examples and case studies.