Predictive systems for water and energy management in irrigation
Description
This 21-hour in-person course expands on the concepts and tools taught in the previous course, "Data Analysis, Optimization and Deep Learning with Python," applying them to the development of predictive systems for efficient water and energy management in irrigation. Participants must have basic knowledge of Python, object-oriented programming (OOP), and agronomy.
In a context where sustainability and energy efficiency are crucial, energy management in irrigation systems has become highly relevant. The integration of renewable energies in irrigation operations and the use of predictive irrigation systems emerge as fundamental solutions to reduce energy consumption and reduce the environmental impact of agricultural practices.
Registration open until October 22
Who is this course for?
- Farmers and ranchers with basic ICT knowledge, agricultural cooperative technicians, irrigation community technicians and agricultural engineers.
- Entrepreneurs, female entrepreneurs and AgrifoodTech Startups.
- University and academic field.
- Professionals from agrotech companies.
- Public officials and agricultural policy makers.
Course leader: Rafael González Perea, PhD in Agricultural Engineering and Assistant Professor at the University of Córdoba (UCO).
Course objectives
- Expand basic knowledge in deep learning.
- Promote the use of tools that add value to the digitalization process in irrigated agriculture.
Promote the application of artificial intelligence to optimize the relationship between water and energy.
PROGRAM | REGISTRATION until October 22.
