• Emphasis on a holistic systems approach and on developing problem-solving skills. A characteristic example is the inclusion of capstone-style courses in each specialization (e.g., Data Science and Artificial Intelligence Applications for the design of end-to-end RAG approaches, Cloud Systems Design to support the role of the Cloud Architect), which combine competencies acquired across multiple courses within each specialization. 
• Emphasis on combining the theoretical and practical (laboratory) components of the curriculum. Students have the opportunity to experiment using the University's available infrastructure, including the data and platform of the University's IoT Smart Campus, featuring more than 200 sensors and 670,000 data values per day, as well as the available HPC/AI clusters.
• Emphasis on open-source technologies and platforms within the Cloud specialization, enabling students to become familiar with their design details, architectures, and internal operation. These tools form the backend of widely used commercial cloud services, allowing students to gain experience both as Cloud users/developers and as Cloud Providers/Cloud Administrators.
• Emphasis on cross-specialization knowledge transfer within the Master's programme. Typical examples include:

a) supporting the transition of AI/ML models from development to production environments (DevOps) by offering Cloud specialization courses (Cloud Platforms and Cloud Native Development) to students in the AI specialization; 

b) applying AI/ML techniques to optimize the production operation of Cloud systems and applications by offering AI specialization courses (Machine Learning and Deep Learning) to students in the Cloud specialization; 

c) studying design considerations and available services for comprehensive digital transformation by offering Cloud specialization courses to students in the Information Systems Management and Digital Transformation specialization; 

d) emphasizing the techno-economic aspects of systems design by offering Information Systems Management courses to students in the Cloud specialization.

 The programme offers multiple scholarship opportunities, as well as both full-time and part-time study options.

• develop a framework for research and teaching cooperation with University Institutions and other institutions in Greece and abroad. 
  • As a result of this effort, a significant number of lecturers come from universities in Greece and abroad, as well as from public or private institutions and organisations.
• to support the travel of students and teaching staff to research centres or Universities in Greece and abroad, for the purpose of conducting research and participating in conferences,
• the promotion of students' research work in international and Greek conferences, where students are invited to present their research work.

• Data Science and Algorithms (Big Data Management, Semantic Web and Knowledge Graphs, Data Mining, Statistics and Applications, Computational Theory, Algorithms and Programming Languages)
• Artificial Intelligence and Machine Learning (Machine Learning Methods and Algorithms, Natural Language Processing, Computer Vision and Robotics, Recommendation Systems
• Advanced Computing Systems (Green Computing, Autonomous, adaptive and human-centered systems, Responsible Computing, Cybersecurity and cryptography)
• Internet of Everything and Next Generation Networks (Internet of Everything Applications and Services, Intelligent Transport Systems and Autonomous Driving, 6G Technology Networks)
• Technology Management - Information Systems (Information Systems Management, Digital Transformation and Innovation, Adoption of Disruptive Technologies, Economics of Emerging Technologies)