The School of Electrical and Computer Engineering of the National Technical University of Athens (NTUA) in collaboration with the Faculties of Applied Mathematics and Natural Sciences, and Civil Engineering, as well as the Faculty of Surveying and Geodesy of NTUA, organizes and operates from 2018 an Interdepartmental Postgraduate Programme of Studies (IPS) in the scientific field of “Data Science and Machine Learning”.

The rapid growth of computing systems (both fixed and mobile) in conjunction with the increasing penetration of wireless and wired networks have resulted in the creation of very large volumes of data on a daily basis. Effective analysis of this data can provide meaningful solutions and help decision-making at various levels.

Data Science itself is at its core an interdisciplinary field with the main focus on managing, analyzing, processing and extracting knowledge from data either in structured or unstructured form. The rapid developments in recent years in the field of data management have led to the emergence of new algorithms and architectures that achieve very large improvements in the speed of processing very large, heterogeneous and constantly changing volumes of data.

Improvements in the performance and speed of computing systems (processors, graphics cards) have resulted in the evolution of machine learning techniques towards fully interconnected networks and deep machine learning, supporting the discovery of increasingly complex patterns and dependencies in data.

As interdisciplinary fields, Data Science and Machine Learning have a direct dependency beyond mathematics and computer science with their scope, which may be related for example to image and video processing and analysis, social network analysis, geospatial data processing, etc.


Bio-Data Analysis

Biomedical data sources and types: wireless sensor networks and smart…