MSc in Data Science (Distance Learning)

The aim of this program is to provide the students with advanced technical skills and a scientific understanding of Data Science. Moreover, the MSc will aid students in developing research competency so they can design their own scientific methods pushing the frontiers of this new emerging field. Finally, special emphasis is given to the development of skills that are required by the relevant cutting-edge industries.

Data Science is an applied science providing innovations and disrupting multiple industries ranging from Information and Communication Technologies and Medicine, to Journalism and Finance. The University of Nicosia has developed partnerships with instructors from the industry and this will enable the development of skills that are currently required by the industry. The MSc will develop full-stack research data scientists that are able to collect requirements, innovate, design, implement and critically evaluate a data science solution.

More specifically, the program aims at:

1. Providing students with the technical and analytical skills required for acquiring, managing, analyzing and extracting knowledge from heterogeneous data sources. Critical skills will be developed that aid students in making decisions on the appropriate data analysis pipeline. Students will be able to collect requirements, design, implement and evaluate a data science solution.
2. Providing students with software engineering and machine learning skills to design and implement scalable, reliable and maintainable solutions for data-oriented problems.
3. Enabling students to develop data programming skills for multiple business domains and possible challenges (Big Data, Streaming Data, Noisy Data, etc.).
4. Enabling students to assess and provide solutions for the privacy and ethical issues that arise at the application of data science methods to many real-world problems.
5. In collaboration with instructors from the industry, the student will be aware of the challenges that a professional comes across when moving from theory to practice and know how to overcome these challenges.
6. Giving the opportunity to the student to work in real world problems with real data in collaboration with industrial partners. Students will gain hands-on experience with the state-of-the-art data science technologies like Deep and Reinforcement learning.
7. Preparing students to pursue a PhD in data science or to any other field where data science skills are required (e.g. bioinformatics, computational social science, data driven journalism, etc.)
8. Providing students with a strong sense of social commitment, global vision and independent self-learning ability.