Subject of the Master’s degree program

The School of Electrical and Computer Engineering, National Technical University of Athens (NTUA) in cooperation with the Schools of Applied Mathematics and Physics, Civil Engineering and Rural and Surveying Engineering, NTUA founded the Interdepartmental Program of Postgraduate Studies (Master’s Degree Program) in the scientific field of “Data Science and Machine Learning” in 2018.

The rapid development of computational systems (both desktop and mobile), in conjunction with the ever-increasing infiltration of the wireless and wired networks have as a result the creation of extraordinary volumes of data on a daily base. The effective analysis of this data can offer substantial solutions and help with decision-making on several levels.

Data Science itself, is basically an inter-scientific field with the main objective of managing, analyzing, processing and extracting knowledge through data either in a structured or non-structured form. The rapid development of the last years in the field of data management has led to the creation of new algorithms and architectures that have immensely improved the speed of processing great, heterogenous and constantly variable volumes of data.

The improvement of performance and speed of computational systems (processors, graphic cards) has had as a result the evolution of machine learning techniques towards the direction of fully interconnected networks and deep machine learning, supporting the discovery of more and more complex patterns and dependencies on data.

As inter-scientific fields, Data Science and Machine Learning have immediate dependency, beyond mathematics and informatics, with their field of implementation, which can be related for example with image and video processing and analysis, analysis of social media, processing of the geospatial data, etc.

Goals of the Master’s degree program

The current Master’s degree program aims to support the intense need which has been noticed during the last years for Master’s degree programs in the field of Data Science and Machine Learning, as it is evident from the increased rates of attendance in related programs from Greek graduates in Universities abroad, with apparent economical consequences. This need is a result of the extended demand that exists in the job market for executives with knowledge in the fields of Data Science and Machine Learning.

In this context, the postgraduate studies offered by this program aim:

--- To deepen the knowledge of engineers and scientists in methods and techniques in the integrated interdisciplinary approach, research and tackling of individual issues of Data Science and Machine Learning, so that executives can be formed/shaped with specialized knowledge in these scientific areas, capable of covering the increasing need of private and public companies, organizations and agencies of the country and other countries, in the multidimensional topics of Data Science and Machine Learning.

--- To the in depth education of engineers and other scientists and the development of their research abilities, in order for them to become sufficient in the production of new knowledge in the field of Data Science and Machine Learning.

 

The graduates of the Master’s degree program obtain, among others, the following knowledge and skills:

--- Theoretical and practical knowledge of methods and technologies in representing, storing and processing heterogeneous types of data with modern algorithmic and computational techniques.

--- Advanced knowledge and skills relevant to the subjects of statistics, probabilities and generally to the mathematical meanings that are required for the comprehension of simple and advanced issues of the under investigation fields, such as knowledge for the use of the most suitable tools for the different sets of data in every occasion.

--- In depth knowledge in the most modern techniques and methodologies that have been presented in the field of Data Science and Machine Learning and that are related to the resolution of problems with techniques of processing and analyzing large volumes of data for the construction of predicting and decision-making models.

--- Scientifically intact summary and effective presentation of the models and the findings that result from the data analysis with Machine Learning methods.

--- Knowledge in specialized fields of implementation (image analysis, computer vision, processing of geospatial coordinates, etc.).

Duration of study

The curriculum is full-time and includes two semesters of courses and one semester of post-graduate Diploma Thesis preparation. The minimum duration of studies is 3 academic semesters and the maximum duration of studies is 2 years including the Diploma Thesis preparation.

Curriculum

To acquire the Master of Science Diploma (MSc) one is required to successfully pass the courses that are equivalent to at least 60 credits in total, and the preparation and successful examination of the Diploma Thesis which is equivalent to 30 more credits.

In total, students are offered a total of 8 mandatory courses and 20 elective courses that emphasize both the comprehension of the theoretical background and the laboratory practice in the fields of Data Science and Machine Learning.

Preparations on the Diploma Thesis start after the end of the first year of studies, with the prerequisite that the post-graduate student has successfully completed until then, at least half of the post-graduate courses of the Master’s degree program. The aim of the Diploma Thesis is the study, the development and the implementation of new methods, technologies and systems of Data Science and Machine Learning, so that the student comprehends the offered knowledge and practice in its real implementation.

Professors

The courses of the program are taught by professors, Scientific and Educational Staff (laboratory and teaching staff) and Technical Research Staff (Specialized Laboratory Technical Staff) of the Schools of Electrical and Computer Engineering, Applied Mathematics and Physics, Civil Engineering and Rural and Surveying Engineering of the NTUA, as well as acknowledged scientists with PhD degrees relevant to the field. Post-graduate students also participate in the teaching process with the preparation of exercises, topics and laboratories. Each course is taught by at least one professor of the Schools of Electrical and Computer Engineering, Applied Mathematics and Physics, Civil Engineering and Rural and Surveying Engineering of the NTUA, with relevant knowledge in their field of research (με σχετικό γνωστικό αντικείμενο). The preparation of the Diploma Thesis of the post-graduate students is supervised by a professor and is examined by a three-member committee.

The chosen professors are acknowledged researchers and have great experience in their field of research, with extensive teaching background, supervision of relevant diploma theses and PhD theses, production of relevant publications in international magazines and conferences and participation in respective research projects (funded or not).

Tuition fees

The students do not pay tuition fees to attend the post-graduate program.