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Computer Science & IT
Data Science (Distance)
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Data Science (Distance)

University of Nicosia
Nicosia, Cyprus
 1206 Points
1 Year, 6 Months

Program Description

The aim of this program is to provide the students with advanced technical skills and a scientific understanding of Data Science. Moreover, the MSc will aid students in developing research competency so they can design their own scientific methods pushing the frontiers of this new emerging field. Finally, special emphasis is given to the development of skills that are required by the relevant cutting-edge industries.

Data Science is an applied science providing innovations and disrupting multiple industries ranging from Information and Communication Technologies and Medicine, to Journalism and Finance. The University of Nicosia has developed partnerships with instructors from the industry and this will enable the development of skills that are currently required by the industry. The MSc will develop full-stack research data scientists that are able to collect requirements, innovate, design, implement and critically evaluate a data science solution.

Entry Requirements

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Bachelor's Degree
Degree from State Technical Institute
English Level
TOEFL (paper based)
Cambridge Proficiency (CPE)
Cambridge Advanced (CAE)

Information about admission:

  • A Bachelor Degree in Computer Science, Computer Engineering, Mathematics, Physics, Biology, Economics, Electrical Engineering, from a recognized university with a CPA of at least 2.5 and transcripts. Applicants with lower CPA will be considered on an individual basis.
  • Personal Statement: A letter highlighting the applicant’s individual competences and strengths and providing his/her reflections regarding the expectations and value of the program as well as to his/her personal advancement and career development.
  • A Curriculum Vitae indicating the student’s education, academic and
  • professional experience, any publications, awards, etc.

Other accepted qualifications:

  • The students should provide proof of knowledge (such as a certificate from a recognized entity or other relevant documentation) of basic programming and basic mathematics (probabilities or statistics or linear algebra or calculus) unless this background is evident from the list of courses in their previous studies. List of Courses undertaken along with the grades received in previous degrees. The applicant should highlight the courses that prove basic knowledge of programming and mathematics. In case there are not such courses, the applicant should submit documentation/certificates from recognized organizations that prove such knowledge;

Other English qualifications and information:

  • Students who do not possess any of the English qualifications or stipulated grades listed above and below and hold IELTS with 4.5 and above, are required to take UNIC’s NEPTON English Placement Test (with no charge) and will receive English Language support classes, if and as needed, from UNIC’s International Gateway Centre (IGC).
  • Computer-based TOEFL – 193 and above
  • Michigan Examination of Proficiency in English (CaMLA) – Pass
  • Pearson PTE General – Level 3 and above
  • KPG (The Greek Foreign Language Examinations for the State Certificate of Language Proficiency) – Level B2 and above
  • Anglia – Level B2 and above
  • IEB Advances Programme English – Pass

Objective of the Program

More specifically, the program aims at:

  • Providing students with the technical and analytical skills required for acquiring, managing, analyzing and extracting knowledge from heterogeneous data sources. Critical skills will be developed that aid students in making decisions on the appropriate data analysis pipeline. Students will be able to collect requirements, design, implement and evaluate a data science solution.
  • Providing students with software engineering and machine learning skills to design and implement scalable, reliable and maintainable solutions for data-oriented problems.
  • Enabling students to develop data programming skills for multiple business domains and possible challenges (Big Data, Streaming Data, Noisy Data, etc.).
  • Enabling students to assess and provide solutions for the privacy and ethical issues that arise at the application of data science methods to many real-world problems.
  • In collaboration with instructors from the industry, the student will be aware of the challenges that a professional comes across when moving from theory to practice and know how to overcome these challenges.
  • Giving the opportunity to the student to work in real world problems with real data in collaboration with industrial partners. Students will gain hands-on experience with the state-of-the-art data science technologies like Deep and Reinforcement learning.
  • Preparing students to pursue a PhD in data science or to any other field where data science skills are required (e.g. bioinformatics, computational social science, data driven journalism, etc.)
  • Providing students with a strong sense of social commitment, global vision and independent self-learning ability.


Semester 1

Data Programming

Mathematics for Data Science

Data Privacy and Ethics

Semester 2

Machine Learning

Managing and Visualizing Data

Research Seminars and Methodology

Project in Data Science

Semester 3

Deep and Reinforcement Learning

Big Data Management and Processing

Artificial Intelligence


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