Data Science and Engineering

Department of Electrical Engineering, Computer Engineering and Informatics

Department of Electrical Engineering, Computer Engineering and Informatics

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Structure

Our M.Sc. Program in Data Science and Engineering aims to provide high quality education to our students, focusing on a subject that will constitute the most significant growth driver of new IT technologies in the following decade, namely the subject of Data Science and Engineering.

The program is carefully designed to satisfy the expectations of major industrial leaders on an international level, and equip our students with all the necessary knowledge and technical skills for them to be successful in world-class research and development projects.

Our 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. Specifically, our students will have the opportunity to enrich their knowledge on advanced subjects revolving around five scientific pillars:

(i) Data analysis using advanced statistical methods (statistical machine learning);

(ii) software and distributed systems;

(iii) computer networks and communications;

(iv) databases;  

(v) hardware.

Modules

Module Description 

First Year

FALL SEMESTER

SPRING SEMESTER

1st Semester

ECTS

2nd  Semester

ECTS

CEI 521  Advanced Topics in Software Engineering 

7

CEI 525  Advanced Topics in Architecture and Parallel Computing

8

CEI 522  Advanced and Distributed Operating Systems

8

CEI 526  Advanced Topics in Data Processing Systems

8

CEI 523 Data Science

8

CEI 527  CSE Research Methodology

7

CEI 524  Network Science

7

Departmental Elective I

7

Total    

30

Total

30

 

SUMMER PERIOD

ECTS

CEI 590 Master Thesis

30

Total

30

Departmental Elective I:

  • CEI 561 Web Information Retrieval 
  • CEI 562 Advanced Topics in Digital Cultural Heritage 
  • CEI 563 Advanced Topics in Parallel and Distributed Processing
  • CEI 565 Software Project Management
  • CEI 568 Computer Graphics: Object Modelling and Reconstruction  
  • CEI 569 Advanced Topics in Computer Security and Cryptography
  • CEI 571 Project Management and Scheduling

For CEI 562 and 563, it is required that the student has not taken a very similar course during his/her undergraduate program. 

Other Departmental Electives:

Alternatively, students can take one of the following departmental electives offered in the Electrical Engineering MSc program:

  • EEN 543 Digital Image Processing
  • EEN 544 Advanced Digital Signal Processing II 
  • EEN 549 Advanced VLSI Design and Embedded Systems 

Admission

Applicants must have an accredited University degree, awarded by an accredited institution in the country where it operates, or a degree evaluated as equivalent to University degree by the Cyprus Council for the Recognition of Higher Education Qualifications (KYSATS). Undergraduate students that are about to graduate can apply for a master’s programme, considering that they expect to receive their University degree before the commencement of the master’s programme.

Applications (early) should be submitted electronically, using the online application system of the University, Student Portal by the 31st of March of 2019.

However, late applications will be assessed depending on availability in each programme.

The following documents are required to be submitted, with the applications:

  • A copy of a valid passport or Civil ID.
  • A Curriculum Vitae (C.V.)
  • Copies of University degrees or a confirmation letter which states that the candidate is expected to graduate before he/she starts the postgraduate programme.
  • Copies of Academic Transcripts
  • A brief Personal Statement of goals and research interests (approximately 500 words) in which the candidate explains why he/she wishes to pursue a graduate programme at CUT.
  • Any other certificates and documents, such as samples of relevant academic or professional work (publications, articles, portfolios etc.) according to the internal rules of graduate studies of each Department where the application is submitted.

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