Computer Science & IT

MSc Big Data Analytics

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Mediterranean College
Athens, Thessaloniki
October 2024, February 2025
1 year full-time or 2 years part-time
Part Time


The programme addresses:
- Graduates of Higher Education Institutions, Colleges or overseas Universities in a Computing or Science, Technology, Engineering, Mathematics (STEM) discipline.
- Graduates of Higher Education Institutions, Colleges or overseas Universities in a Business discipline.
Also, graduates of theoretical sciences (social sciences, humanities) or health sciences may be admitted to the program conditionally and upon successful completion of a bridging course offered by the School of Computing.

Requirements for registration:

  • Copy of the last studies certificate *
  • CV (in English)
  • Reference Letters (2)
  • Good knowledge of English (IELTS 6.5 level or equivalent) **
  • Academic interview
  • Photos (2)
  • Copy of ID-card/ passport

* Candidates without a first degree in computing are also encouraged to apply for the programme. Factors such as the possession of a degree in other disciplines or other professional qualifications, proven experience in computing, and commitment to continuing personal & professional development may contribute to the admission to the programme.

** Candidates without official English language certificates can sit the English language placement test of Mediterranean College.


The MSc Big Data Analytics is a perfectly structured programme that equips students with both the theoretical grounding and the practical skills concerning a broad range of topics related to Big Data Analytics.

Big data is around us. Every day 2.5 quintillion (2,500 followed by 15 zeros) bytes of data are created, and 90% of the data in the world today has been generated in the last two years. As a consequence, skills in processing and obtaining intelligence from the precious commodity of big data are in demand across many sectors, ranking data scientist as the best job in America according to Glassdoors 2018 rankings and for three years running.

The main focus of the programme is the extraction, analysis, exploitation and management of information from big data, using a variety of scientific techniques and software tools. A key aspect of the programme is that its structure and learning outcomes are designed in conjunction with SAS, the global leaders in data analytics, whose data mining and business intelligence platform is widely used in academia and industry.

The programme is designed for graduates in a science, technology, engineering or mathematics subject (STEM), who want to gain the necessary background in Big Data Analytics, but also for data analysis professionals who want to expand their knowledge and skills in this specific discipline. Thus, this specific programme provides exciting career opportunities in academia or industry.

The programme is studied within 2 years in a part-time basis and comprises of six 20-credit modules and a diploma thesis of 60 credits. A key aspect of the programme is that its structure and learning outcomes are designed in conjunction with SAS Analytics. The whole programme is brought together by an in-depth project through the Independent Scholarship module in an area of your choice, which may be focused on your current role if you are studying part time, or in an area where you see your career developing.


Graduates of the programme, according to Greek legislation, are holders of an accredited master’s degree, professionally equivalent to those awarded by Greek State Higher Education Institutions. If they wish so, they can have their degree recognised by the Greek authorities. Click here for more information on the degree recognition procedure.

Graduates have excellent employment and earnings potential as prospects include working in many areas of computing and information technology, particularly in the areas of data analytics, business intelligence, information management, and visualization, having an in-depth knowledge and critical understanding of the key issues and concepts in today’s data-driven business and science landscapes. Alternatively, they may undertake further research leading to a PhD.

For information regarding student fees please contact the Institute.
Interested? Fill in the contact form and an advisor from the Institute will get in touch with you shortly.