Doctoral Studies
DICL accepts applications for graduate doctoral studies twice a year, typically in March and November, for entering the program in the Fall and Spring semester, respectively. The application process is handled by the Studies and Student Affairs department of the Cyprus University of Technology.
Info: PhD Programmes
M.Sc. GRADUATE STUDIES
M.Sc. in Artificial Intelligence and Data Engineering
The Master’s programme in Artificial Intelligence and Data Engineering aims to provide high-level academic education and applied expertise in two of the most important and rapidly evolving areas of Computer Science and Engineering: Artificial Intelligence (AI) and Data Engineering. The programme is designed to address the current needs of industry and the labour market, both in Cyprus and internationally, and to equip students with the necessary knowledge and skills for scientific, technological, and professional advancement. The key objective of the programme is to cultivate professionals with specialised skills that are not only in high demand, but also essential in today’s landscape, both by major global companies and by leading research centres and universities with strong research and development activity.
Info: MSc in Artificial Intelligence and Data Engineering
CEI 526 - Scalable Data Processing Systems
The need to store and process massive amounts of data has led to the evolution of existing database systems while a new breed of data processing systems has emerged. This course covers a spectrum of topics from core techniques in relational data management to highly-scalable data processing using parallel database systems and distributed processing systems such as MapReduce and Spark. First, the course covers the basic principles in database query processing and optimization, including index structures, sort and join processing, query rewrites, and physical plan selection. Next, the course covers topics from parallel and distributed databases, including data partitioning and distributed join algorithms. Finally, the course covers scalable data processing systems and NoSQL databases (column, document, and key-value stores). The course material will be drawn from textbooks as well as recent research literature.
Undergraduate Courses
CEI 325 - Database Systems
The course provides a solid database background focusing on relational database management systems. Topics include data modeling, database design theory and methodology, entity-relationship model, normalization, data definition and manipulation languages (SQL), storage and indexing techniques, and transaction processing. The course also covers fundamentals of database management systems architecture and methods for database application development.
CEI 226 - Algorithms and Complexity
The course focuses on the design and analysis of efficient algorithms and their complexity. In particular, the course covers various topics including algorithm analysis, asymptotic analysis, recurrence relations, divide-and-conquer algorithms, dynamic programming, greedy algorithms, graph representation, graph search, minimum spanning trees, shortest paths, maximum flow, and NP-Completeness. Prerequisite background: Data Structures.
