What is a degree in Data Science and Engineering?
- The emergence of internet, cloud and multimedia technologies as an integral part of everyday life, both in the workplace and in the field of personal life, results in huge volumes of data being produced by users of information systems on a daily basis. The recording and storage of this data by the providers of these information systems/services is now a routine process, due to the now petty cost of large database systems.
- Based on these developments, the technological, scientific and business challenge of our time is the development of large-scale analysis systems. That is, systems that have the ability to process in real-time large volumes of data in order to extract useful information of very high added value to guide decision-making processes. Highly competitive knowledge economy industries such as social networks, search engines, large companies developing prototype drugs, large university hospitals, defense systems companies, but also banking sector (risk assessment, capital management) as well as large retail companies, are typical cases of organizations where huge volumes of data are collected on a daily basis. Intelligent analysis of the exploitation of this data could lead to significant new value-added chains for these organizations.
- With highly conservative estimates, it is predicted that considering only the US, in the next three years will there be a shortage of graduates with high-level skills related to the analysis and extraction of value-added information from large volumes of data that will grow to 190,000 people. In addition, it is estimated that more than 1.5 million additional jobs will be left vacant in dynamically growing enterprises, due to the huge shortage of graduate managers and analysts with average-level know-how in the subject of analysis and management of large amounts of data with a view to extracting information on timely and efficient decision-making at strategic and management level.
- In light of the above, the new MSc program offered in Data Science and Engineering of the Cyprus University of Technology aims to create the first generation of graduates in the European South with those high-level qualifications that will be allow them to claim a competitive share in the international division of work in this fast-growing and very well-paid subject of Data Science and Engineering.
- In addition to theoretical training, students will have the opportunity to apply their new knowledge to interdisciplinary projects, simulating the real working conditions of the Scientist and Data Engineer. They will thus develop their skills in the use of the most modern tools and analytical methods, as well as how the results of the analysis should be best utilized by an organization. That is, in ways that can lead to a complete change in the model of business strategies and decision-making processes with a view to increasing their competitiveness at the international level.
The graduates of our program will be able to:
- Formulate the most appropriate questions that can be answered using the data available in an organization, and to interpret the results of their decision-making analysis in a correct and strategic way.
- Develop and manage efficiently very large-scale data storage and recovery systems.
- Develop appropriate models of statistical machine learning to draw high value-added conclusions and forecast future trends/behaviours using the available data.
- Develop and implement efficient software systems for the analysis of large-scale real-time data.
- Understand the legal and ethical dimensions and obligations arising from data management and analysis related to privacy and security issues.
- Be able to choose the appropriate hardware architectures for the purposes of data analysis of each different organization.
Graduates of the Master of Science and Data Engineering will have the professional skills to take leadership positions in the industry such as telecommunications, computer and software companies, robotics, pharmaceuticals, Bioinformatics educational institutions and government allotted organizations. They will also be able to set up their own businesses or even continue their studies at doctoral level.
Why study Data Science and Engineering at CUT?
- In September 2015, the Department offered the pioneering for the data of Cyprus and the wider area of Southern Europe master's degree in Data Science and Engineering of the Cyprus University of Technology. In 2015 it was the first Master's degree in data science in Greece, Italy, Spain, Cyprus, Malta, and the Balkans.
- Data Science and Engineering is the new, dynamically emerging technological and scientific field that aims to develop methods and technologies to successfully and effectively address precisely these challenges. Therefore, it is no coincidence that it has been called upon by many leading intellectuals (such as Emeritus Professor of the University of California, Berkeley, Prof. Hal Varian), by leaders of some of the world's largest business giants ( like former Google CEO Eric Schmidt, and from the world's largest consulting firm (McKinsey and co.) as the most attractive job of the 21st century.
- This program is offered by a combination of experienced academics, with extensive international experience that concerns all aspects of the subject of Data Science and Engineering. These aspects include large-scale data processing, storage, and management systems, high-complex statistical analysis methods and systems to predict and conclude in uncertainty environments, optimal decision-making techniques based on the results of the analysis, as well as large-scale network theory in the light of the inference and analysis of large-scale systems. The curriculum is designed following the example of the corresponding programs offered at some of the world's largest universities (e.g., University of California, Berkeley and Stanford University), but trying to emphasize both The Cyprus and European specificities where necessary.
- Our postgraduate program is in full alignment with the National Strategy for digitizing the economy and is key to the strategic pillar for the development of Information and Communication Technologies of the national research strategy. At the same time, it is manifestly aligned with the National and European AI Strategy. Lastly, it is fully aligned with the university's objectives pertaining to research, educational and business innovations in the fields of advanced information and communication technologies.
