The agrifood system stands as an important sector worldwide. Encompassing all the food supply chain facets – from cultivation to consumption – it includes food and beverages processing/production, farming, retail, transportation, packaging, and more. Yet, it faces several challenges, due to natural resources scarcity, population growth, labour productivity and climate impact are responsible for several challenges in the agrifood sector. In response, innovation emerges as essential for this field’s progress, to meet the demands while being aligned with environmental concerns.
The AI & Agrifood Business online course intends to explore artificial intelligence and machine learning, associated with computer vision, as technologies for overcoming challenges in the agrifood systems. This course will also introduce important business concepts, for creating a synergy between Deep Tech and business development.
Objectives
Provide knowledge and specialized training on Artificial Intelligence and Machine Learning.
Present business concepts associated with Deep Tech based solutions.
The main objective of this course is to expose students to theoretical and practical examples of how to use AI, machine learning, and deep learning, associated with visual data acquisition, focused on applications within the agrifood sector. Furthermore, essential business concepts will be explored, to unlock the potential to transform innovation into business opportunities.
This course was developed as part of the DIP4Agri project, coordinated by the Universidade Católica Portuguesa, with the support of the following partners: Wageningen University, Aarhus University, Food for Sustainability, FME (The Netherlands), BGI – Building Global Innovators, Planície Verde, and Castillo de Canena.
Funding
The Deep Tech Innovators course is financially supported by the EIT HEI Initiative – Innovation Capacity Building for Higher Education, funded by the European Union.
Contactos
G. Estudos Avançados e Formação
E-mail: formacaoavancada.porto@ucp.pt
Tel: 22 619 62 02
2ª a 5ª: 9h30-12h30 e 14h30-17h30
6ª: 9h30-12h30 e 14h30-19h00
Sáb: 9h30-12h30
Mais Informação
Dates
May 2024: 3, 17 and 24
Shedule
Fridays: 10:00 am - 5:00 pm (WET)
(6 and 4 hours workload)
Format
Online
Contactos
G. Estudos Avançados e Formação
E-mail: formacaoavancada.porto@ucp.pt
Tel: 22 619 62 02
2ª a 5ª: 9h30-12h30 e 14h30-17h30
6ª: 9h30-12h30 e 14h30-19h00
Sáb: 9h30-12h30
Mais Informação
Dates
May 2024: 3, 17 and 24
Shedule
Fridays: 10:00 am - 5:00 pm (WET)
(6 and 4 hours workload)