Interdepartmental Master’s Program (IMSP) Computational Data & Decision Sciences

Since the academic year 2018–19, the new Interdepartmental Master’s Program (IMP) in Computational Data and Decision Sciences (Greek acronym: ΥΔΑ, English title: Data Driven Computing and Decision Making) has been offered by the University of Patras (Government Gazette 1695/B/16-05-2018), in accordance with Law 4485/2017 (Government Gazette 114/A).

The Program is jointly organized by the following Departments of the University of Patras:

  • Department of Computer Engineering and Informatics, School of Engineering (also responsible for administrative support of the Program).
  • Department of Mathematics, School of Natural Sciences.

The Program aims to provide specialized interdisciplinary postgraduate education in topics related to data, its management and processing in modern computing systems, and the extraction of knowledge and decision-making based on data.

The curriculum consists of five (5) compulsory courses, three (3) elective courses, and the completion of a Master’s Thesis, corresponding to a total of 90 ECTS credits.

The duration of the Program leading to the award of the Master of Science (MSc) degree is three (3) academic semesters.

The Program accepts graduates from Greek higher education institutions and recognized equivalent institutions abroad, including graduates of:

  • Computer Engineering and Informatics Departments,
  • Electrical and Computer Engineering Departments,
  • Electrical/Electronic Engineering and Computer Engineering Departments,
  • University Departments of Computer Science,
  • Departments of Natural and Technological Sciences with a specialization in either Computer Science or Statistics,
  • Departments of Engineering Schools, and
  • Departments of Economics and Business Schools.

Graduates of Higher Military Educational Institutions, as well as graduates of former Technological Educational Institutes (ATEI) with a related academic background, are also eligible for admission.

In all cases, applicants are expected to possess a strong mathematical background and adequate knowledge of programming and statistics.