This is a platform for the project ASSISTANT training program on Challenge Based Learning in Artificial Intelligence Enhanced Digital Transformation Curricular. 

The aim of the program is directly related to the ASSISTANT project objectives, that are: (1) to increase the number of courses on Digital transformation curricular, (2) to increase of using intelligence technologies in education by developing virtual assistant, (3) to increase HE learners’ experience on digital transformation settings supported with catboats, (4) to increase awareness on benefits and implementation practices. 

Courses developed (1) Big data, (2) Digital education, (3) Artificial intelligence, (4) Robotics and IoT.


ASSISTANT project has been funded with support from the European Commission under the Erasmus+ Programme. This document  reflects the views only of the author, and the Commission cannot be held responsible for any use which may be made of the information contained therein.

Robotics and IoT

Relevance: Robotics and Internet of Things (IoT) are changing more and more all areas of life. Automation and real-time data exchange enable smart solutions in healthcare, manufacturing, logistics and many other areas by increasing efficiency, precision and interconnectivity. However, these technologies also pose significant risks, such as privacy invasion, security threats, and potential job loss. To harness the transformative potential of Robotics and IoT, it is therefore crucial to understand their risks and to practice a responsible and ethical approach.

Objective: the course aims to provide a comprehensive understanding of IoT and Robotics, their different fields of applications, ethical implications, technical foundation and basic skills to design and model IoT and Robotics solutions.  

Learning outcome: By the end of the course, students will have acquired sufficient knowledge of Robotics and the Internet of Things, enabling them to use these key technologies of the 21st century to solve challenging problems.


Big data

Relevance: Information technologies with growing amounts of digital storage and more devices or sensors than ever before have resulted in massive quantities of diverse data, where applying this data for many useful purposes becomes challenging. Term Big Data indicates massive and often unstructured data, for which traditional data management and analysis tools are insufficient. 

The aim of the course is to give an an overview of the Big Data concept and main techniques for working with it effectively. Practical focus is on extracting value and formulating data-driven insights using analytics and visualization. 

Learning outcome: by the end of the course, students should have a sufficient knowledge of big data analytics as a tool for addressing research questions and approaching challenging problems with data-driven solutions.