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.



M.Sc. in Data Science and Engineering

The M.Sc. in Data Science and Engineering Program aims to provide high quality education to students, focusing on a subject that will constitute the most significant growth driver of new IT technologies in the following decade. The program is carefully designed to satisfy the expectations of major industrial leaders on an international level, and equip students with all the necessary knowledge and technical skills for them to be successful in world-class research and development projects. The ultimate goal is to create a new generation of high caliber Computer Science professionals, with unique sets of skills that will render them internationally competitive for the decades ahead, and attractive to the most reputable IT companies worldwide.

CEI 526 - Advanced Topics in 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 MapReduce. 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 such as MapReduce and NoSQL databases (column, document, and key-value stores).

Undergraduate Courses

CEI 325 - Database Systems

The course gives a solid background in databases with a focus on relational database management systems. Topics include data modeling, database design theory and methodology, data definition and manipulation languages, storage and indexing techniques, query processing and optimization, transactions, concurrency control, and recovery. The course also covers fundamentals of database management system architecture and techniques 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, NP-Completeness, and approximation algorithms. Prerequisite background: Data Structures.

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