Master of Science in Data Science and Machine Learning (DAMA)
HELLENIC OPEN UNIVERSITY
Full time, Part time
Earliest start date
The study program “Data Science and Machine Learning” aims at delivering knowledge and developing skills in state-of-the-art methods and computing tools in Data Science and Machine Learning, in an accessible manner and by promoting active learning.
DAMA focuses on hands-on computational applications of these methods, utilizing data from all modern scientific fields (natural sciences, engineering, informatics, humanities, and life sciences). Students will be hands-on practicing using programming tools and up-to-date computing tools. DAMA aims to combine knowledge of fundamental concepts and techniques with specific applications so that its graduates will be aptly skilled in today’s labor and market.
Overview of the Programme
Classification according to UNESCO’s ISCED-2011
Based on the level of Education: 7
Classification according to UNESCO ISCED-2013
0619: Information and Communication Technologies (ICTs) not elsewhere classified
ECTS credit points
The total sum of ECTS units (European Credit Transfer and Accumulation System) required for the completion of the Program is 120.
The minimum time required for the completion of the Programme is two (2) academic years.
Type of Postgraduate Study Programme
- Master of Science (M.Sc.)
- Level 7 according to the EQF (European Qualifications Framework)
The official language of the Program is English. The language in which all material content is presented, written assignments are submitted, and related communication is carried out, is English.
- DAMA50 Mathematics for Machine Learning
- DAMA51 Foundations in Computer Science
- DAMA60 Algorithmic Techniques and Systems for Data Science and Machine Learning
- DAMA61 Numerical and Computational Techniques for Data Science and Machine Learning
Module Selection Guidelines
- The Programme is structured in two (2) years, which include four (4) compulsory course modules. Students may choose one (1) to two (2) course modules each academic year.
- The choice of the first-year course modules is unrestrained; there is no priority constraint in selecting between DAMA50 and DAMA51.
- The selection of DAMA60 and DAMA61 becomes possible after attending the course modules of the first year (i.e. a student can select any module of a year as long as he/she has completed all modules of the preceding year or he/she registers for any remaining earlier modules).
- There is no priority constraint in selecting between DAMA60 and DAMA61.
- For the acquisition of the Master’s Degree, successful attendance of the four compulsory course modules is required.
Upon successful completion of the program, graduates will have gained:
- An understanding of the basic principles and methods of Data Science and Machine Learning.
- An ability to use methods to collect, manage and analyze large volumes of data (big data).
- An ability to analyze big data and use it for classification and prediction purposes.
- An ability to use machine learning methods and optimization algorithms for decision-making.
- An ability to develop machine learning algorithms for specific applications in a variety of scientific fields.
- An ability to use advanced methods for presenting findings to ensure the most effective analysis and communication.
An understanding of the social and ethical aspects of analyzing and presenting data, privacy protection, data management taking into account the regulatory framework governing such activities using computers, and the protection of intellectual property.