Master in Data Science (MSc) (Online) - University Nicosia

• 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.
• Providing students with software engineering and machine learning skills to design and implement scalable, reliable and maintainable solutions for data-oriented problems.
• Enabling students to develop data programming skills for multiple business domains and possible challenges (Big Data, Streaming Data, Noisy Data, etc.).
• 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.
• 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.
• 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.
• 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.).
• Providing students with a strong sense of social commitment, global vision and independent self-learning ability.

Upon successful completion of this Master in Data Science (MSc), the student is expected to:

• Critically collect requirements, design, implement, and assess the performance of a data science solution.
• Conduct research and develop novel methods for Data Science or any other interdisciplinary field that requires Data Science skills (e.g. Bioinformatics, Data driven journalism, computational social science, business intelligence).
• Identify and communicate the issues of data privacy and ethics as they rise from specific real-world applications. The graduates will be able to synthesize solutions that alleviate those issues.
• Communicate and collaborate with teams on interdisciplinary problems. The graduate will be able to communicate on low, technical level but also on a high, non-technical level.
• Design solutions real world challenges of data mining (big data, streaming data, heterogeneous data, noisy data, etc.).
• Synthesize reports and presentations for communicating analysis results and debating on data-driven decisions.
• Define, compare, and combine recent research developments in data science, machine learning and artificial intelligence and invent novel potential applications with social and business value.