Application possibilities of data-analysis in the field of food safety course in English
(In Hungarian: Az adatelemzés alkalmazási lehetőségei az élelmiszerlánc-biztonság területén)

General aim of the course:

Assessing the safety of the food chain, analysing risks and, where appropriate, managing them, requires increasingly complex, computationally intensive analyses and methods. The overall objective of the course is to familiarise students with the range of computational methods applicable to food chain safety: basics, their applications and limitations.

The last two classes wil be held on 15 December between 14.15-16.00, in the Urbányi Béla lecture hall, Building C. The topics of the classes are:
– Food chain data analysis, driver analysis. Process-mining, Bayesian network analysis. Case study: automated driver analysis and alerting system for dairy production chain.
– Decision preparation. Data visualisation, interpretation and communication of results. Representing limitations and uncertainty. Ethical considerations. Decision-making processes.
– The food chain analyst of the future: challenges, new areas. Big data, application possibilities and limitations of artificial intelligence (AI). Case study: literature research using AI.

Lecturer: Ákos Jóźwiak (DFI)