Name:
Building Capacity in AI and Robotics in Universities of Partner Countries
Leader:
University of Pisa
Description:
The goal of this work package is to offer specialized training to faculty members in partner universities on up-to-date topics pertaining to the newly proposed or modified courses offered in the respective MSc and
BSc programs. Training entails both the technical aspect of the course and the transfer of knowledge of teaching such topics to students given the experience of European partners. Due to the ongoing pandemic
and travel restrictions, all training conducted thus far was mostly online.
Tasks:
Achievements
• An online training course on the Python Programming Language was organized by the University of Genoa and presented by Alberto Cabrio / Vega Research Laboratories (July – August 2021)
• An online training course on Robotic Operating Systems was organized by the University of Pisa and offered by Alessandro Settimi (November – December 2021)
• An online training course on Introduction to Machine Learning was organized by the University of Genoa and offered by Stefano Rovetta (February 2022)
• An online training course on Introduction to Data Science was organized by the University of Granada and offered by Jorge Casillas (February 2022)
• An advanced hybrid training course (in-person and online) was organized by the University of Granada and offered by a team of experts: Prof. Manuel Pegalajar-Cuellar, Prof. Daniel Molina Cabrera, Prof. Alberto Fernández, Prof. Salvador García, and Mr. Germán González (May 2022). The training covered the following topics:
− Time Series with Python
− Supervised and Unsupervised Learning with Python
− Learning from imbalanced data with
− Singular learning problems with Python
− Data Pre-processing with Python
• Two hybrid workshops (in-person and online) were organized by the University of Genoa / Department of Informatics, Bioengineering, Robotics, and Systems Engineering (July 2022). The courses were given by Prof. Nicoletta Noceti and Prof. Francesca Odone:
− Introduction to NNs, CNNs, Autoencoders, GANs, RNNs, and Transformers.
− Introduction to computer vision, digital signals and images, image filters and features, CNNs for image classification, and motion/depth estimation.
*A three-day practical training course was organized by the Institute for Technical and Computational Mechanics (ITM) at the University of Stuttgart (October 2022) on Control Systems and Robotics and Knowledge Transfer on Practical Teaching Methods. The training comprised of four experiments with focus given on teaching methods, assessment, and experiment development. The four experiments were related to Mobile robotics, Railway Locomotive Distance Control, Balancing Ball on a Rim and Pendulum movement control.