The Postgraduate Studies Programme in "Data and Web Science" (DWS) offers a specialization in the emerging fields of Data Science and Web Science. This is crucial given that the exponentially increasing data production and the rapid evolution of Web technologies pose new challenges in multiple thematic areas of Computer Science. These challenges are posed at all levels of the IT technology stack in terms of infrastructure, management, access, and utilization of information for knowledge extraction that will be provided directly and will open up new possibilities for the development of science and innovation.
In order to obtain the Postgraduate Specialization Diploma of the Postgraduate Programme "Data and Web Science" of the School of Informatics is required within the maximum period of time provided in Article 5 of the internal operating regulations of the programme (<https://dws.csd.auth.gr/files/internal-regulation-gr.pdf>), the concentration of ninety (90) credits (ECTS). Sixty (60) ECTS come from courses. The thirty (30) ECTS are attributed to the Postgraduate Diploma Thesis which is assigned during the third semester and is is graded by a three-member examination committee.
The primary scope of the Programme is the adequate training of postgraduate students in Data and Web Science so that they are able to either work directly in industry in relevant jobs, or to proceed with research activities in academia towards a Ph.D. Also the Programme contains a flexible curriculum that includes basic as well as advanced topics and offers strong resources in the areas of Data and Web Science.
In addition to the basic knowledge, graduates will have the ability to: 1) apply knowledge in practice, 2) communicate in a second language 3) search, analyze and synthesize data and information, using appropriate technologies, 4) adapt to new situations and take decisions 5) work independently or in a team in an international and/or interdisciplinary environment, 6) generate new ideas and scientific knowledge, design and manage scientific and research projects, 7) respect diversity, multiculturalism and the natural environment), 8) demonstrate professional, social and moral responsibility, and gender sensitivity, 9) apply critique and self-critique, and 10) promote free, productive and deductive thinking.