Exploring Digital Asset Management and Tokenization (TRUST-FOOD)
"Exploring Digital Asset Management and Tokenization" is part of the courses developed by the TRUST-FOOD project with the aim of empowering SMEs to up- and re-skill with improved understanding of blockchain technology. The TRUST-FOOD project, funded under the DIGITAL Europe Programme of the European Union, builds and makes available short-term training courses for SME employees' up- and re-skilling activities - with a focus on SME owners, managers and those working in the food supply chain sector.
Why this course?
The aim of the course is to provide an overview of the concept of digital assets and tokenization within the context of the food supply chain - and explore the different ways in which blockchain technology can help alleviate efficient digital asset management and tokenization within the food industry. The course begins with a foundational objective, which is to ensure that participants gain a solid understanding of the fundamentals of digital assets and tokenization. This knowledge is then contextualised within the food supply chain, highlighting the relevance and application of these concepts in this specific area. A significant part of the course is dedicated to exploring how blockchain technology can be utilised to manage digital assets efficiently and facilitate the process of tokenization in the food industry. This exploration will not only cover theoretical aspects but also delve into practical applications, demonstrating how blockchain can transform the way digital assets are handled in the food sector.
Learning outcomes
The course bridges the gap between theory and practice: it focuses on the application of the acquired knowledge about digital assets and tokenization to real-world scenarios in the food supply chain. This objective is crucial as it allows learners to translate their understanding into practical skills that can be applied in real-life situations, enhancing the relevance and impact of their learning experience.
The course is split in 14 lectures and 8 quizzes and takes around 5 hours to complete.
