Master of Science (MS) in Data Science

Analyze, visualize, communicate 

Over 90% employability rate

Applications are now open for Fall Term 2024

Application Deadline: Rolling admissions
Upcoming Deadline: June 14, 2024
Start Date: September 23, 2024

Program Overview

The MS in Data Science is an advanced program of study that prepares students for a professional career in Information Technology, particularly in handling big volumes of data, finding patterns in data, making predictions, and effectively visualizing and communicating data, with the intent to facilitate organizational decision-making. Students become acquainted with various types of data including business transaction data, text data, and images.

The program equips participants with a well-calibrated, theoretical, and practical synthesis of applied mathematics, statistics, computer science, and business information skills. It is appropriate for students from a variety of backgrounds, including information technology, computer science, engineering, economics, MIS, as well as business.

Prospective students are expected to have some basic with some basic programming and mathematics knowledge.

The program is available in a campus-based education modality.

  • Duration: One year (full-time) or up to three years (part-time).
  • Number of Courses: 12 courses (36 US credits).
  • Attendance: Classes run Monday to Thursday, from 18:30-21:30. Fridays are reserved for make-up classes and other academic activities, such as master classes, workshops, lectures, talks, etc.
  • Admission points: New students are admitted at the start of the fall, winter and spring terms.

Unique Program Features

  • NECHE Accreditation
  • Hands-on experience and practice in lab settings.
  • Free software through Microsoft alliance
  • Instructors with international teaching and research experience
  • Appropriate for students with a non-IT background with preparatory bridge courses

Program Structure (Curriculum)

Required Courses:

  • Introduction to Big Data
  • Exploring and Analyzing Data
  • Applied Machine Learning
  • Data Visualization
  • Knowledge Graphs
  • Big Data Architectures
  • Search Engines and Web Mining
  • Machine Vision in Data Science
  • Natural Language Processing

Two of the following electives:

  • Leadership Development and Strategic Thinking for Data Scientists
  • Business Forecasting
  • Deep Learning
  • Machine Learning and Applications
  • ITC 6230 Deep Learning
  • ITC 6125 Machine Learning and Applications

Required Project – Year 2:

Capstone Project OR Thesis

Program Level Competencies

Upon successful completion of this program, participants should be able to:

  • Critically evaluate the techniques for storing and processing big volumes of data, including transaction business data, text data, and images and to apply the relevant tools.
  • Analyze the basic machine learning techniques and apply the relevant tools.
  • Articulate business problems using data science techniques.
  • Design a comprehensive data science solution and assess it both from a technical and a business perspective.
  • Successfully complete a research project in big data or in data science.
  • Formulate ideas and arguments and communicate them effectively both in writing and orally in an academic or business context
  • Undertake programming at an advanced level: use advanced algorithms, practice distributed computing, use of no-SQL databases.

Click here to download the learning outcomes

Tuition & Scholarships


Tuition is payable on a course by course basis. The cost for the full program is 9,720€.

For complete information about our tuition and fees click here.

Merit Scholarships

The School of Graduate & Professional Education offers scholarships covering a portion of the cost of tuition to all applicants who have demonstrated exceptional academic performance in their undergraduate studies.

For complete information about our merit scholarships click here.

Financial Assistance

Since its founding in 1875, The American College of Greece (ACG) has provided assistance to students needing help in meeting their educational expenses, thereby enabling students with demonstrated ability and promise to access a quality education, regardless of their financial circumstances.

For more information about financial assistance click here.


All ACG alumni are entitled to a 10% tuition fee discount on top of any other scholarship of financial assistance program which may apply.

Corporate discount programs are also available to two or more employees from one organization who wish to study in our graduate programs.

For more information about corporate click here.

Student Profile

The program is ideal for recent university or college graduates of information technology, engineering, economics, and science, or for working professionals in IT who wish to advance their career in data science or big data. Students coming from different backgrounds, such as business or social sciences, are also encouraged to apply.  Students who do not have previous programming or mathematical/statistical background may be asked to complete courses from the Graduate Certificate in Computer Science, which provides them with the basic foundations required to enter the program.

Current Student profile

Average Age: 28.04 years
Female: 27%
Male: 73%
Student Nationality: Domestic: 94%; International: 6%
First degree obtained from: Greek AEI (56.25%); ACG-Deree (14.06%); International University (17.19%)

Career Opportunities

There is great demand for Data Scientists in Greece as well as internationally. Graduates of the program pursue careers in the field of data science and analytics such as: Business Data Analysist, Data Engineer, Data Scientist, and Big Data Engineer. Furthermore, they are employed in companies specializing in information technologies, finance and insurance,  retail settings, professional services, manufacturing, start-ups and more.

Deree graduate students receive support from the Office of Career Services, which help them connect with the 50,000 ACG alumni around the globe, expand their professional network, and gain access to various job positions.


  • Elena Chatzimichali
    Full-time Faculty - School of Graduate and Professional Education
    Information Technology (IT)
  • Maira Kotsovoulou
    Full-time Faculty - School of Liberal Arts and Sciences
    Information Technology (IT)
  • Dimitris Vogiatzis
    Full-time Faculty - School of Liberal Arts and Sciences
    Information Technology (IT)
  • Constantinos B. Papadias Constantinos B. Papadias
    Associate Faculty - School of Liberal Arts and Sciences
    Information Technology (IT)
  • Ioannis Christou
    Full-time Faculty - School of Liberal Arts and Sciences
    Information Technology (IT)
  • Georgios Drakakis
    Part-time Faculty - School of Liberal Arts and Sciences
    Information Technology (IT)
  • Sofoklis Efremidis
    Part-time Faculty - School of Graduate and Professional Education
    Information Technology (IT)
  • Andreas Zaras
    Part-time Faculty - School of Graduate and Professional Education
    Information Technology (IT)

Admission Requirements

The minimum graduate admission requirements are:

1. A bachelor's degree from an accredited institution in Science, Engineering, Information Technology, Economics, or Business with an average grade of B or better. Applicants with an undergraduate degree in a discipline other than these above may still be admitted after completing some pre-required courses on the advice of the program co-ordinator. 

2. Evidence of strong motivation to undertake graduate-level study in Data Science to be determined by the interview and the personal statement submitted with the application form.

3. Proficiency in the English language evidenced through one of the following: TOEFL, IELTS, or Proficiency. DEREE College graduates and graduates from other accredited English-speaking institutions are not required to submit evidence of Proficiency in the English language.

Credit Transfer:
Credit transfer from previously attended graduate degree programs of accredited institutions, may be allowed at a maximum limit of 9 credits and will be examined on an individual basis.

Note: The MS in Data Science program is eligible for Title IV federal aid.​

Download Brochure

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Request Additional Info

Tel.: +30 210 600 2208
E-mail: [email protected]

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