From data to knowledge
- We live in the era of data and modern Web technologies! The phrase “big data is the new oil” highlights the influence of big data in today’s economy, in a time where people and machines interact through modern technologies over the World Wide Web.
- Technology has entered all fields of life and work and has led to an avalanche of data everywhere, while social Web technologies have led to new experiences of continuous interaction among people and machines.
- Data are produced everywhere and continuously, e.g. in smart cities equipped with sensors, in social networks, in intelligent vehicles in transportation means, in health organizations.
- The General Data Protection Regulation (GDPR) emphasizes the importance of data and the challenging demands for their protection and their ethical use.
- Multiple challenges arise in scientific, social and practical level, as we produce more data than what we can process and exploit!
- There is an international need to strengthen the skills and knowledge of young scientists to empower them such that they understand the data and master the technologies for data analysis and discovery of valuable knowledge.
Data and web science specialization strengthens young scientists
- Data Science and Web Science have already been established and are evolving internationally! The School of Informatics at Aristotle University has planned and will offer (pending approval from the Ministry of Education) a cutting edge Masters of Science (MSc) programme on Data and Web Science (DWS), starting from the academic year 2018-19.
- The DWS dynamic programme of studies spans on 3 semesters, and uses English as its official language.
- The first two semesters are devoted to courses which follow effective teaching methodologies (part of the lectures are done with online distant learning), requiring the undertaking of projects on state-of-the-art research and development topics covering all technology stacks of data and web concepts (infrastructure, services, technologies, methods, algorithms, tools). Each student must choose 4 courses per semester from a high quality list of courses aligned with international curricula standards, which indicatively contains:
|SEMESTER A||SEMESTER B|
|Machine Learning||Web data mining|
|Big data analysis technologies||Semantic Web|
|Distributed Data Processing||Big data knowledge mining|
|Text mining and Natural Language Processing||Decentralized technologies – Blockchains|
|Social networks analytics||Advanced Machine Learning|
- In the 3rd semester students undertake their MSc diploma thesis on state of the art topics in the areas of data analytics and web technologies aiming at a quality result leading to either a scientific publication or to a tool/technology that could be turned into a product. Particular emphasis is put on diploma theses in collaboration with the industry for solving real-world problems.
- Students will be updated and engaged in activities related to the multitude of international collaborations and projects of the DWS faculty members who serve at the Web, Data and Knowledge Engineering sector of the School of Informatics.
- Entrance requirements: Bachelor degree in a related to DWS subject. If the degree has been obtained outside Greece then students must secure its recognition by the Hellenic NARIC (http://www.doatap.gr/en/) by the end of the programme, in order to be awarded their MSc.
- There is also the option of following the DWS programme as a part-time student, with the duration of the programme being extended accordingly.
- Tuition fees are 600 euro per semester (300 per semester in part-time mode).
Beyond the DWS MSc
Following the successful completion of the DWS master, graduates will be able to work in organization in Greece and abroad in jobs like:
- Data scientists, in organizations requiring analysis and interpretation of their data, covering a vast range of domains (health, transportation, automotive, …)
- Social networks expert, for trend detection in social media
- GDPR expert in organizations maintaining and curaing data
- Technical manager for data and web on any field and with specialization on new technologies (e.g. blockchains)
- Data and Web technologies curator in organizations managing data
- Data and web software engineers
- Researcher in European and international R&D projects
Applicants Selection Criteria:
- BSc grade average and degree/diploma type along with degrees earned at the Undergraduate courses which are directly relevant to the MSc program concepts with a criterion weight 40%. It is noted that the degree/diploma grade average should be at least 6 (in the grade scale of 0-10) or its equivalent in another grading scale system.
- Personal interview evaluation by the DWS MSc Selection Committee with a criterion weight 25%
- Grade and type of undergraduate diploma/degree thesis with a criterion weight 10%
- Research and professional experience, potential publications and the scientific authorship record of the applicant with a criterion weight 15%
- Foreign language speaking, with emphasis on English language capacity with a criterion weight 10%
The teaching staff of the Web, Data and Knowledge Engineering sector: