- Artificial Intelligence & Machine Learning
- Statistics & Mathematics
- Database and Big Data technology
- Software Development & Algorithmics
However, the above list is not exhaustive, as a data scientist often needs to employ other skills, such as hacking, coding, critical thinking, problem understanding etc. All those make the job of the data scientist to be a mashup of different skills that are rarely found together. Students who apply for the MSc in Data Science of the International Hellenic University, are mainly graduates with a STEM (Science, Technology, Engineering and Mathematics) or an Economics degree, who have a background in statistics and a good knowledge of fundamental concepts of databases and programming. The courses of the programme are taught exclusively in English. The academic staff comes from Universities in Greece and abroad. Official Government Gazette: Re-establishment PDF (in Greek) Regulation PDF (in Greek)
Start date: October 2021
Application deadline: September 2021 or until places are filled
Campus: Thermi, Thessaloniki
Duration/Mode: 14 months (full-time) or 26 months (part-time)/ weekdays evenings
Taught language: English
Entry requirements: An undergraduate degree from an accredited University
Language requirements: IELTS (academic 6.5 and above), TOEFL (IBT, 90 and above) or TOEIC (850 and above) score, or a recognised by the Greek State certificate of proficiency in English
Fees: 3,700€ (total)
How to apply: Programme announcement
Who can apply
To be considered for the programme, candidates are required to have:
Upon arrival at the IHU all students follow an intensive foundation course titled “Applied Mathematics in ICT” that aims to bring all incoming students to the same level with respect to some of the mathematics knowledge that is required to excel in the programme. During the first term, all students are required to attend five mandatory core courses. During the second term, all students follow a further three required courses and a combination of two elective courses. Finally, during the third term, work is dedicated exclusively to the Master’s dissertation.
The core courses
1st Term Core Courses
- Programming for Data Science
- Data Science for Business: Theory and Practice
- Statistical Methods for Data Science
- Machine Learning Principles and Concepts
- Advanced Database Systems
2nd Term Core Courses
The elective courses
During the second term students tailor their programme further by choosing elective courses. The choice of elective courses must sum up to 12 ECTS (2 courses). Some of the elective courses may not be offered in a particular year, depending entirely on student demand. 2nd Term Elective Courses
- Natural Language Processing and Text Mining
- Information Retrieval
- Advanced Machine Learning
- Knowledge Management in the Web
- Multimedia Data Analysis
- Exploratory Data Analysis and Visualization
- Social Media and Online Community Management
- Consulting Project
During the third term, students work on their Masters Dissertation project, the thematic area of which is relevant to their programme of studies and their interests. The dissertation provides a good opportunity to apply theory and concepts learned in different courses to a real-world Data Science problem or challenge. Students are supervised throughout their projects by a member of the academic faculty and the academic assistants. After submission of the dissertation, students present their projects to classmates and faculty at a special event.
Duration of studies
The MSc in Data Science (full-time) is a 14-month programme taught over three terms. Lectures mainly take place on weekday evenings. The MSc in Data Science programme is also available in part-time mode over 26 months for those who cannot commit to a full-time programme either for work or other reasons.
The Academic Faculty
|Dr Eleni Heracleous Associate Professor Dean|
|Professor Panayiotis Bozanis +30 2310 807501 email@example.com|
|Professor Periklis Chatzimisios +30 2310 807501 firstname.lastname@example.org|
|Dr Maria Drakaki Associate Professor +30 2310 807524 email@example.com|
|Dr Christos Tjortjis Associate Professor +30 2310 807576 firstname.lastname@example.org|
|Dr Vassilios Peristeras Assistant Professor +30 2310 807539 email@example.com|
|Dr Dimitrios Tzetzis Assistant Professor +30 2310 807548 firstname.lastname@example.org|
Other Research and Teaching Personnel
|Dr Christos Berberidis Research and Teaching Staff +30 2310 807534 email@example.com|
|Dr Dimitrios Baltatzis Research and Teaching Staff firstname.lastname@example.org|
|Dr Stavros Stavrinides Research and Teaching Staff email@example.com|
|Dr Georgios Martinopoulos Academic Associate +30 2310 807533 firstname.lastname@example.org|
|Dr Leonidas Akritidis Academic Associate|
|Dr Dimitrios Karapiperis Academic Associate|
|Dr Katerina Tzafilkou Academic Associate|
|Dr Apostolos Ampatzoglou||University of Groningen|
|Dr. Agamemnon Baltagiannis||Principal Data Scientist – Team Leader, Global Data Science Hub, SAP|
|Dr Nikolaos Bassiliades||Associate professor Department of Informatics, Aristotle University of Thessaloniki, Greece|
|Professor Georgios Doukidis||Athens University of Economics and Business, Greece|
|Dr Dimitris Drossos||Assistant Professor University of the Aegean, Greece|
|Dr Konstantinos Fouskas||University of Macedonia, Greece|
|Professor George M. Giaglis||Athens University of Economics and Business, Greece|
|Dr Christos Kalloniatis||University of the Aegean, Greece|
|Dr Merkouris Karaliopoulos||Research Fellow, CERTH/ITI Visiting Research Fellow, Dept. of Informatics, Athens University of Economics and Business|
|Professor Vasilis Katos||Bournemouth University|
|Professor Sokratis Katsikas||University of Piraeus, Greece|
|Dr Paris Kokorotsikos||Euroconsultants S.A.|
|Dr Ioannis Magnisalis||IT strategy and planning officer, European Commission, Team Data scientists’ leader / Research Associate at International Hellenic University|
|Dr Michela Meo||Associate Professor Politecnico di Torino|
|Dr Maria Papadopouli||Associate Professor University of Crete|
|Dr Athanasia Pouloudi||Associate Professor Information Systems Management Athens University of Economics and Business (AUEB)|
|Dr Katerina Pramatari||Assistant Professor Department of Management Science and TechnologyAthens University of Economics and Business|
|Dr Panagiotis Rizomiliotis||Assistant Professor, University of the Aegean|
Fees & Financing
The programme fees for the MSc in Data Science is 3,700€ (pending approval). The amount is payable in two instalments for the full time mode or in four instalments for the part time mode at the beginning of each semester. The fees are also eligible for financing through LAEK 0,45% – OAED programme.
If you have been accepted to a postgraduate programme, you will need to make a payment of the deposit of 500 Euros to secure your place. This amount will count towards the first instalment of your tuition fees. The deposit is non-refundable once you have commenced your studies at the IHU. Prior to that, a refund can be made but a 20% administrative fee will be retained. The deposit can be paid by bank transfer or bank draft. Credit card payments can be made through electronic banking (contact your Bank as handling fees may apply).
The School of Science & Technology offers a number of scholarships for the programmes it offers, covering a significant proportion of the fees. These scholarships are competitive. Award criteria include the quality of the first degree, the undergraduate grades of the candidate, his/her command of the English language and overall profile. Candidates for scholarships should include a separate letter with their application documents in which they request to be considered for a scholarship, stating the reasons why they think they qualify.
Programme announcement – Admissions
Next MSc in Data Science class starts in October 2021. Interested parties are invited to submit their application by September 2021 or until places are filled, by following instructions at the page ‘Apply to UCIPS’.
Ideal Career path
According to the European Commission’s European Data Market study the number of “data companies” as well as the need for “data workers” are already high and it is expected to grow even more in the near future. Depending on the focus of your study and skills, there are several career paths you can follow; the list below, although it is non-exhaustive, it covers the spectrum of roles you can play in an organisation:
- Data Management Professional: Focuses on managing the infrastructure and storage of (usually big) data.
- Data Engineer/Data Architect: Focuses on the design and implementation of (usually big) data infrastructure, choosing the right database and cloud technologies and deploying them to serve the analytics needs of the organization.
- Business Analyst: Focuses on the analytics part, trying to process data to build models to form useful and actionable insights. It includes anything related to Business Intelligence, such as creating reports, dashboards etc.
- Data Analyst/Data Scientist: Focuses on developing and applying machine learning and statistical models on the data at hand. They need to have coding skills, with Python and R being the most popular options right now as well as knowledge of algorithmics, statistics and databases.
- Machine Learning Researcher: Focuses on developing and testing predictive and descriptive models from data. They need to have a deep understanding of machine learning and statistics to run experiments and evaluate the results. Machine learning research positions are available not only in universities (e.g. PhD candidateships, PostDoc Associates etc.) but also in industry as big companies are being staffed with analytics researchers who try to create custom models for their needs instead of using off-the-shelf products and applying sub-optimal, generic solutions.
In addition to technical skills gained through study, our students benefit from the University’s excellent Careers Office in order to attain essential soft skills (e.g. communication skills, interview preparation, CV writing etc.) to better prepare for the job market.
The MSc in Data Science takes place in the facilities of the School of Science & Technology of the University Center of International Programmes of Studies of the International Hellenic University in Thermi-Thessaloniki.
Postal address: School of Science & Technology Department of School of Science & Technology University Center of International Programmes of Studies 14th km Thessaloniki – Nea Moudania 570 01 Thermi, Thessaloniki, Greece Tel: +30 2310 807 529/526 Email: : email@example.com