The DWS M.Sc. Programme
The main topic of the DWS M.Sc. Programme is the specialization in Data and Web Science. The efficient and effective data management is a critical issue given the exponential data growth and the rapid evolution of Web technologies which pose new challenges. These challenges arise at all levels of the Information Technology Stage in terms of infrastructure, management, access, and exploitation of information for knowledge mining that will be provided in a direct way and will open new possibilities for the development of science and innovation.
The purpose of the DWS M.Sc. Programme is the training of postgraduate students in Data Science and the World Wide Web so that they are either able to work directly in the industry in relevant jobs, or to undertake research and PhD theses. We are aiming for a flexible curriculum that includes both basic and advanced topics and offers powerful resources in the areas of Data Science and Web Science.
Who Can Apply
Holders of first cycle degrees (Universities and Technological Educational Institutions) in from Departments of an area related to the topic of the Programme (e.g., Computer Science, Mathematics, Engineering, etc). The number of students admitted to the postgraduate program “Data and Web Science” for the academic year 2019-2020 is set at a maximum of forty (40) postgraduate students.
I. The GPA, the type of Diploma and the performance in undergraduate courses directly related to the Postgraduate Program with a 40% rate. It is emphasized that the minimum GPA of Undergraduate Diploma must be equivalent to the grade of six (6) in the 0-10 scale.
II. The performance in the personal interview of the candidate by the Committee with a rate of 25%.
III. The performance and type of Diploma Thesis of the candidate at a rate of 10%.
IV. The research experience, professional experience, publications at a rate of 15%.
V. The applicant’s language skills at a rate of 10%.
The Programme at a Glance
1st Semester: Machine Learning, Technologies for Big Data Analytics, Distributed Data Management, Text Mining and Natuaral Language Processing, Social Network Analysis
2nd Semester: Web Mining, Semantic Web, Mining from Massive Datasets, Decantralized Technologies, Advanced Topics in Machine Learning, Advanced Topics in Databases
3rd Semester: Diploma Thesis